{"text": "Resnik ( 1995 ) reported a correlation of r = .9026.10 The results are not directly comparable , because he only used noun-noun pairs , words instead of concepts , a much smaller dataset , and measured semantic similarity instead of semantic relatedness .", "citing_paper_id": "W06-1104", "cited_paper_id": "External_3502", "citing_paper_year": 2006, "cited_paper_year": 1995, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "using information content to evaluate semantic similarity", "cited_author_ids": ["Philip Resnik"], "citing_author_ids": null, "extended_context": "This correlation coefficient is an upper bound of performance for automatic SR measures applied on the same dataset . Resnik ( 1995 ) reported a correlation of r = .9026.10 The results are not directly comparable , because he only used noun-noun pairs , words instead of concepts , a much smaller dataset , and measured semantic similarity instead of semantic relatedness . Finkelstein et al. 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because he only used noun-noun pairs , words instead of concepts , a much smaller dataset , and measured semantic similarity instead of semantic relatedness .", "citation_id": "W06-1104_27", "citation_excerpt_index": 0, "section_name": "experiments"}
{"text": "Similar observation for surface word frequency was also observed by ( Bertram et al. , 2000 ; Bradley , 1980 ; Burani et al. , 1987 ; Burani et al. , 1984 ; Schreuder et al. , 1997 ; Taft 1975 ; Taft , 2004 ) where it has been claimed that words having low surface frequency tends to decompose .", "citing_paper_id": "P13-3018", "cited_paper_id": "External_90447", "citing_paper_year": 2013, "cited_paper_year": 1980, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "lexical representation of derivational relation", "cited_author_ids": ["D Bradley"], "citing_author_ids": null, "extended_context": "( Taft , 1975 ) with his experiment on English inflected words , argued that lexical decision responses of polymorphemic words depends upon the base word frequency . Similar observation for surface word frequency was also observed by ( Bertram et al. , 2000 ; Bradley , 1980 ; Burani et al. , 1987 ; Burani et al. , 1984 ; Schreuder et al. , 1997 ; Taft 1975 ; Taft , 2004 ) where it has been claimed that words having low surface frequency tends to decompose . Later , Baayen ( 2000 ) proposed the dual processing race model that proposes that a specific morphologically complex form is accessed via its parts if the frequency of that word is above a certain threshold of frequency , then the direct route will win , and the word will be accessed as a whole .", "section_number": 3, "section_title": null, "intent": "Background", "cite_marker_offset": [94, 108], "sents_before": [[{"index": 1, "word": "Similar", "lemma": "similar", "after": " ", "pos": "JJ", "characterOffsetEnd": 584, "segment_span": [0, 46], "characterOffsetBegin": 577, "originalText": "Similar", "ArgType": null, "before": " "}, {"index": 2, "word": "observation", "lemma": "observation", "after": " ", "pos": "NN", "characterOffsetEnd": 596, "segment_span": [0, 46], "characterOffsetBegin": 585, "originalText": "observation", "ArgType": null, "before": " "}, {"index": 3, "word": "for", "lemma": "for", "after": " ", "pos": "IN", "characterOffsetEnd": 600, "segment_span": [0, 46], 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was also observed by ( Bertram et al. , 2000 ; @@CITATION ; Burani et al. , 1987 ; Burani et al. , 1984 ; Schreuder et al. , 1997 ; Taft 1975 ; Taft , 2004 ) where it has been claimed that words having low surface frequency tends to decompose .", "citation_id": "P13-3018_2", "citation_excerpt_index": 0, "section_name": "related work"}
{"text": "But their importance has grown far beyond machine translation : for instance , transferring annotations between languages ( Yarowsky and Ngai 2001 ; Hwa et al. 2005 ; Ganchev , Gillenwater , and Taskar 2009 ) ; discovery of paraphrases ( Bannard and Callison-Burch 2005 ) ; and joint unsupervised POS and parser induction across languages ( Snyder and Barzilay 2008 ) .", "citing_paper_id": "J10-3007", "cited_paper_id": "N01-1026", "citing_paper_year": 2010, "cited_paper_year": 2001, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "inducing multilingual pos taggers and np bracketers via robust projection across aligned corpora", "cited_author_ids": ["David Yarowsky", "Grace Ngai"], "citing_author_ids": null, "extended_context": "MT system combination ( Matusov , Ueffing , and Ney 2006 ) . But their importance has grown far beyond machine translation : for instance , transferring annotations between languages ( Yarowsky and Ngai 2001 ; Hwa et al. 2005 ; Ganchev , Gillenwater , and Taskar 2009 ) ; discovery of paraphrases ( Bannard and Callison-Burch 2005 ) ; and joint unsupervised POS and parser induction across languages ( Snyder and Barzilay 2008 ) . IBM Models 1 and 2 and the HMM are simple and tractable probabilistic models , which produce the target sentence one target word at a time by choosing a source word and generating its translation .", "section_number": 1, "section_title": null, "intent": "Motivation", "cite_marker_offset": [124, 146], "sents_before": [[{"index": 1, "word": "But", "lemma": "but", "after": " ", "pos": "CC", "characterOffsetEnd": 59, "segment_span": [0, 62], "characterOffsetBegin": 56, "originalText": "But", "ArgType": null, "before": " "}, {"index": 2, "word": "their", "lemma": "their", "after": " ", "pos": "PRP$", "characterOffsetEnd": 65, "segment_span": [0, 62], "characterOffsetBegin": 60, "originalText": "their", "ArgType": null, "before": " "}, {"index": 3, "word": "importance", "lemma": "importance", "after": " ", "pos": "NN", "characterOffsetEnd": 76, "segment_span": [0, 62], "characterOffsetBegin": 66, "originalText": "importance", "ArgType": "subj", "before": " "}, {"index": 4, "word": "has", 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{"text": "Previous sentiment-analysis work in different domains has considered inter-document similarity ( Agarwal and Bhattacharyya , 2005 ; Pang and Lee , 2005 ; Goldberg and Zhu , 2006 ) or explicit", "citing_paper_id": "W06-1639", "cited_paper_id": "W06-3808", "citing_paper_year": 2006, "cited_paper_year": 2006, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "seeing stars when there aren’t many stars graphbased semisupervised learning for sentiment categorization", "cited_author_ids": ["A B Goldberg", "J Zhu"], "citing_author_ids": null, "extended_context": "Relationships between the unlabeled items Carvalho and Cohen ( 2005 ) consider sequential relations between different types of emails ( e.g. , between requests and satisfactions thereof ) to classify messages , and thus also explicitly exploit the structure of conversations . Previous sentiment-analysis work in different domains has considered inter-document similarity ( Agarwal and Bhattacharyya , 2005 ; Pang and Lee , 2005 ; Goldberg and Zhu , 2006 ) or explicit inter-document references in the form of hyperlinks ( Agrawal et al. , 2003 ) .", "section_number": 6, "section_title": null, "intent": "Background", "cite_marker_offset": [154, 177], "sents_before": [[{"index": 1, "word": "Previous", "lemma": "previous", "after": " ", "pos": "JJ", "characterOffsetEnd": 1976, "segment_span": [0, 31], "characterOffsetBegin": 1968, "originalText": "Previous", "ArgType": null, "before": " "}, {"index": 2, "word": "sentiment-analysis", "lemma": "sentiment-analysis", "after": " ", "pos": "NN", "characterOffsetEnd": 1995, "segment_span": [0, 31], "characterOffsetBegin": 1977, "originalText": "sentiment-analysis", "ArgType": null, "before": " "}, {"index": 3, "word": "work", "lemma": "work", "after": " ", "pos": "NN", "characterOffsetEnd": 2000, "segment_span": [0, 31], 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{"text": "However , the method we are currently using in the ATIS domain ( Seneff et al. 1991 ) represents our most promising approach to this problem .", "citing_paper_id": "J92-1004", "cited_paper_id": "H91-1014", "citing_paper_year": 1992, "cited_paper_year": 1991, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "development and preliminary evaluation of the mit atis systemquot", "cited_author_ids": ["S Seneff", "J Glass", "D Goddeau", "D Goodine", "L Hirschman", "H Leung", "M Phillips", "J Polifroni", "V Zue"], "citing_author_ids": null, "extended_context": "Exactly how to get from the parse tree to an appropriate meaning representation is a current research topic in our group . However , the method we are currently using in the ATIS domain ( Seneff et al. 1991 ) represents our most promising approach to this problem . We have decided to limit semantic frame types to a small set of choices such as CLAUSE ( for a sentence-level concept , such as request ) , PREDICATE ( for a functional operation ) , REFERENCE ( essentially proper noun ) , and QSET ( for a set of objects ) .", "section_number": 3, "section_title": null, "intent": "Uses", "cite_marker_offset": [65, 83], "sents_before": [[{"index": 1, "word": "However", "lemma": "however", "after": "", "pos": "RB", "characterOffsetEnd": 2216, "segment_span": [0, 26], "characterOffsetBegin": 2209, "originalText": "However", "ArgType": null, "before": " "}, {"index": 2, "word": ",", "lemma": ",", "after": " ", "pos": ",", "characterOffsetEnd": 2217, "segment_span": [0, 26], "characterOffsetBegin": 2216, "originalText": ",", "ArgType": null, "before": ""}, {"index": 3, "word": "the", "lemma": "the", "after": " ", "pos": "DT", "characterOffsetEnd": 2221, "segment_span": [0, 26], "characterOffsetBegin": 2218, "originalText": "the", "ArgType": null, "before": 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{"text": "The ICA system ( Hepple , 2000 ) aims to reduce the training time by introducing independence assumptions on the training samples that dramatically reduce the training time with the possible downside of sacrificing performance .", "citing_paper_id": "N01-1006", "cited_paper_id": "P00-1036", "citing_paper_year": 2001, "cited_paper_year": 2000, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "independence and commitment assumptions for rapid training and execution of rulebased pos taggers", "cited_author_ids": ["M Hepple"], "citing_author_ids": null, "extended_context": "2.1.2 The ICA Approach The ICA system ( Hepple , 2000 ) aims to reduce the training time by introducing independence assumptions on the training samples that dramatically reduce the training time with the possible downside of sacrificing performance . 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{"text": "To this end , several toolkits for building spoken dialogue systems have been developed ( Barnett and Singh , 1997 ; Sasajima et al. , 1999 ) .", "citing_paper_id": "W00-1017", "cited_paper_id": "External_46366", "citing_paper_year": 2000, "cited_paper_year": 1999, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "europa a generic framework for developing spoken dialogue systems", "cited_author_ids": ["Munehiko Sasajima", "Yakehide Yano", "Yasuyuld Kono"], "citing_author_ids": null, "extended_context": "One of the next research goals is to make these systems task-portable , that is , to simplify the process of porting to another task domain . To this end , several toolkits for building spoken dialogue systems have been developed ( Barnett and Singh , 1997 ; Sasajima et al. , 1999 ) . 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{"text": "Thus , over the past few years , along with advances in the use of learning and statistical methods for acquisition of full parsers ( Collins , 1997 ; Charniak , 1997a ; Charniak , 1997b ; Ratnaparkhi , 1997 ) , significant progress has been made on the use of statistical learning methods to recognize shallow parsing patterns syntactic phrases or words that participate in a syntactic relationship ( Church , 1988 ; Ramshaw and Marcus , 1995 ; Argamon et al. , 1998 ; Cardie and Pierce , 1998 ; Munoz et al. , 1999 ; Punyakanok and Roth , 2001 ; Buchholz et al. , 1999 ; Tjong Kim Sang and Buchholz , 2000 ) .", "citing_paper_id": "W01-0706", "cited_paper_id": "External_29000", "citing_paper_year": 2001, "cited_paper_year": 1999, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "cascaded grammatical relation assignment", "cited_author_ids": ["S Buchholz", "J Veenstra", "W Daelemans"], "citing_author_ids": null, "extended_context": "While earlier work in this direction concentrated on manual construction of rules , most of the recent work has been motivated by the observation that shallow syntactic information can be extracted using local information by examining the pattern itself , its nearby context and the local part-of-speech information . Thus , over the past few years , along with advances in the use of learning and statistical methods for acquisition of full parsers ( Collins , 1997 ; Charniak , 1997a ; Charniak , 1997b ; Ratnaparkhi , 1997 ) , significant progress has been made on the use of statistical learning methods to recognize shallow parsing patterns syntactic phrases or words that participate in a syntactic relationship ( Church , 1988 ; Ramshaw and Marcus , 1995 ; Argamon et al. , 1998 ; Cardie and Pierce , 1998 ; Munoz et al. , 1999 ; Punyakanok and Roth , 2001 ; Buchholz et al. , 1999 ; Tjong Kim Sang and Buchholz , 2000 ) . Research on shallow parsing was inspired by psycholinguistics arguments ( Gee and Grosjean , 1983 ) that suggest that in many scenarios ( e.g. , conversational ) full parsing is not a realistic strategy for sentence processing and analysis , and was further motivated by several arguments from a natural language engineering viewpoint .", "section_number": 2, "section_title": null, "intent": "Background", "cite_marker_offset": [548, 570], "sents_before": [[{"index": 1, "word": "Thus", "lemma": "thus", "after": "", "pos": "RB", "characterOffsetEnd": 375, "segment_span": [0, 63], "characterOffsetBegin": 371, "originalText": "Thus", "ArgType": null, "before": " "}, {"index": 2, "word": ",", "lemma": ",", "after": " ", "pos": ",", "characterOffsetEnd": 376, "segment_span": [0, 63], "characterOffsetBegin": 375, "originalText": ",", "ArgType": null, "before": ""}, {"index": 3, "word": "over", "lemma": "over", "after": " ", "pos": "IN", "characterOffsetEnd": 381, "segment_span": [0, 63], 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{"text": "Task properties Determining whether or not a speaker supports a proposal falls within the realm of sentiment analysis , an extremely active research area devoted to the computational treatment of subjective or opinion-oriented language ( early work includes Wiebe and Rapaport ( 1988 ) , Hearst ( 1992 ) , Sack ( 1994 ) , and Wiebe ( 1994 ) ; see Esuli ( 2006 ) for an active bibliography ) .", "citing_paper_id": "W06-1639", "cited_paper_id": "External_32379", "citing_paper_year": 2006, "cited_paper_year": 1992, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "directionbased text interpretation as an information access refinement", "cited_author_ids": ["M Hearst"], "citing_author_ids": null, "extended_context": "Note that from an experimental point of view , this is a very convenient problem to work with because we can automatically determine ground truth ( and thus avoid the need for manual annotation ) simply by consulting publicly available voting records . Task properties Determining whether or not a speaker supports a proposal falls within the realm of sentiment analysis , an extremely active research area devoted to the computational treatment of subjective or opinion-oriented language ( early work includes Wiebe and Rapaport ( 1988 ) , Hearst ( 1992 ) , Sack ( 1994 ) , and Wiebe ( 1994 ) ; see Esuli ( 2006 ) for an active bibliography ) . In particular , since we treat each individual speech within a debate as a single `` document '' , we are considering a version of document-level sentiment-polarity classification , namely , automatically distinguishing between positive and negative documents ( Das and Chen , 2001 ; Pang et al. , 2002 ; Turney , 2002 ; Dave et al. , 2003 ) .", "section_number": 2, "section_title": null, "intent": "Background", "cite_marker_offset": [288, 303], "sents_before": [[{"index": 1, "word": "Task", "lemma": "Task", "after": " ", "pos": "NNP", "characterOffsetEnd": 764, "segment_span": [0, 3], "characterOffsetBegin": 760, "originalText": "Task", "ArgType": null, "before": " "}, {"index": 2, "word": "properties", "lemma": "property", "after": " ", "pos": "NNS", "characterOffsetEnd": 775, "segment_span": [0, 3], "characterOffsetBegin": 765, "originalText": "properties", "ArgType": "subj", "before": " "}, {"index": 3, "word": "Determining", "characterOffsetEnd": 787, "after": " ", "pos": "VBG", 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{"text": "Various approaches for computing semantic relatedness of words or concepts have been proposed , e.g. dictionary-based ( Lesk , 1986 ) , ontology-based ( Wu and Palmer , 1994 ; Leacock and Chodorow , 1998 ) , information-based ( Resnik , 1995 ; Jiang and Conrath , 1997 ) or distributional ( Weeds and Weir , 2005 ) .", "citing_paper_id": "W06-1104", "cited_paper_id": "External_3502", "citing_paper_year": 2006, "cited_paper_year": 1995, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "using information content to evaluate semantic similarity", "cited_author_ids": ["Philip Resnik"], "citing_author_ids": null, "extended_context": "Various approaches for computing semantic relatedness of words or concepts have been proposed , e.g. dictionary-based ( Lesk , 1986 ) , ontology-based ( Wu and Palmer , 1994 ; Leacock and Chodorow , 1998 ) , information-based ( Resnik , 1995 ; Jiang and Conrath , 1997 ) or distributional ( Weeds and Weir , 2005 ) . 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{"text": "Both tasks are performed with a statistical framework : the mention detection system is similar to the one presented in ( Florian et al. , 2004 ) and the coreference resolution system is similar to the one described in ( Luo et al. , 2004 ) .", "citing_paper_id": "W05-0709", "cited_paper_id": "P04-1018", "citing_paper_year": 2005, "cited_paper_year": 2004, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "a mentionsynchronous coreference resolution algorithm based on the bell tree", "cited_author_ids": ["Xiaoqiang Luo", "Abe Ittycheriah", "Hongyan Jing", "Nanda Kambhatla", "Salim Roukos"], "citing_author_ids": null, "extended_context": "It is these orthographic variations and complex morphological structure that make Arabic language processing challenging ( Xu et al. , 2001 ; Xu et al. , 2002 ) . 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@@CITATION , Halliday and Hasan 1976 , Longacre 1979 , Haberlandt et al. 1980 ) , all of them share a certain limitation in their formal techniques for analyzing paragraph structure .", "citation_id": "J91-2003_5", "citation_excerpt_index": 0, "section_name": "introduction"}
{"text": "Thus , over the past few years , along with advances in the use of learning and statistical methods for acquisition of full parsers ( Collins , 1997 ; Charniak , 1997a ; Charniak , 1997b ; Ratnaparkhi , 1997 ) , significant progress has been made on the use of statistical learning methods to recognize shallow parsing patterns syntactic phrases or words that participate in a syntactic relationship ( Church , 1988 ; Ramshaw and Marcus , 1995 ; Argamon et al. , 1998 ; Cardie and Pierce , 1998 ; Munoz et al. , 1999 ; Punyakanok and Roth , 2001 ; Buchholz et al. , 1999 ; Tjong Kim Sang and Buchholz , 2000 ) .", "citing_paper_id": "W01-0706", "cited_paper_id": "External_5861", "citing_paper_year": 2001, "cited_paper_year": 1997, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "a linear observed time statistical parser based on maximum entropy models", "cited_author_ids": ["A Ratnaparkhi"], "citing_author_ids": null, "extended_context": "While earlier work in this direction concentrated on manual construction of rules , most of the recent work has been motivated by the observation that shallow syntactic information can be extracted using local information by examining the pattern itself , its nearby context and the local part-of-speech information . Thus , over the past few years , along with advances in the use of learning and statistical methods for acquisition of full parsers ( Collins , 1997 ; Charniak , 1997a ; Charniak , 1997b ; Ratnaparkhi , 1997 ) , significant progress has been made on the use of statistical learning methods to recognize shallow parsing patterns syntactic phrases or words that participate in a syntactic relationship ( Church , 1988 ; Ramshaw and Marcus , 1995 ; Argamon et al. , 1998 ; Cardie and Pierce , 1998 ; Munoz et al. , 1999 ; Punyakanok and Roth , 2001 ; Buchholz et al. , 1999 ; Tjong Kim Sang and Buchholz , 2000 ) . Research on shallow parsing was inspired by psycholinguistics arguments ( Gee and Grosjean , 1983 ) that suggest that in many scenarios ( e.g. , conversational ) full parsing is not a realistic strategy for sentence processing and analysis , and was further motivated by several arguments from a natural language engineering viewpoint .", "section_number": 2, "section_title": null, "intent": "Background", "cite_marker_offset": [189, 207], "sents_before": [[{"index": 1, "word": "Thus", "lemma": "thus", "after": "", "pos": "RB", "characterOffsetEnd": 375, "segment_span": [0, 63], "characterOffsetBegin": 371, "originalText": "Thus", "ArgType": null, "before": " "}, {"index": 2, "word": ",", "lemma": ",", "after": " ", "pos": ",", "characterOffsetEnd": 376, "segment_span": [0, 63], "characterOffsetBegin": 375, "originalText": ",", "ArgType": null, "before": ""}, {"index": 3, "word": "over", "lemma": "over", "after": " ", "pos": "IN", "characterOffsetEnd": 381, "segment_span": [0, 63], 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"NN", "characterOffsetEnd": 1925, "segment_span": [13, 24], "characterOffsetBegin": 1917, "originalText": "analysis", "ArgType": null, "before": " "}, {"index": 25, "word": ".", "lemma": ".", "after": " ", "pos": ".", "characterOffsetEnd": 1926, "characterOffsetBegin": 1925, "originalText": ".", "ArgType": null, "before": ""}]], "cleaned_cite_text": "Thus , over the past few years , along with advances in the use of learning and statistical methods for acquisition of full parsers ( Collins , 1997 ; Charniak , 1997a ; Charniak , 1997b ; @@CITATION ) , significant progress has been made on the use of statistical learning methods to recognize shallow parsing patterns syntactic phrases or words that participate in a syntactic relationship ( Church , 1988 ; Ramshaw and Marcus , 1995 ; Argamon et al. , 1998 ; Cardie and Pierce , 1998 ; Munoz et al. , 1999 ; Punyakanok and Roth , 2001 ; Buchholz et al. , 1999 ; Tjong Kim Sang and Buchholz , 2000 ) .", "citation_id": "W01-0706_31", 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{"text": "We experiment with four learners commonly employed in language learning : Decision List ( DL ) : We use the DL learner as described in Collins and Singer ( 1999 ) , motivated by its success in the related tasks of word sense disambiguation ( Yarowsky , 1995 ) and NE classification ( Collins and Singer , 1999 ) .", "citing_paper_id": "P07-1068", "cited_paper_id": "External_5983", "citing_paper_year": 2007, "cited_paper_year": 1995, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "unsupervised word sense disambiguation rivaling supervised methods", "cited_author_ids": ["D Yarowsky"], "citing_author_ids": null, "extended_context": "Learning algorithms . We experiment with four learners commonly employed in language learning : Decision List ( DL ) : We use the DL learner as described in Collins and Singer ( 1999 ) , motivated by its success in the related tasks of word sense disambiguation ( Yarowsky , 1995 ) and NE classification ( Collins and Singer , 1999 ) . We apply add-one smoothing to smooth the class posteriors .", "section_number": 2, "section_title": null, "intent": "Motivation", "cite_marker_offset": [242, 257], "sents_before": [[{"index": 1, "word": "We", "lemma": "we", "after": " ", "pos": "PRP", "characterOffsetEnd": 622, "segment_span": [0, 59], "characterOffsetBegin": 620, "originalText": "We", "ArgType": "subj", "before": " "}, {"index": 2, "word": "experiment", "lemma": "experiment", "after": " ", "pos": "NN", "characterOffsetEnd": 633, "segment_span": [0, 59], "characterOffsetBegin": 623, "originalText": "experiment", "ArgType": "verb", "before": " "}, {"index": 3, "word": "with", "lemma": "with", "after": " ", "pos": "IN", "characterOffsetEnd": 638, "segment_span": [0, 59], "characterOffsetBegin": 634, "originalText": "with", "ArgType": null, "before": " "}, {"index": 4, "word": "four", "lemma": "four", "after": " ", "pos": "CD", "characterOffsetEnd": 643, "segment_span": [0, 59], "characterOffsetBegin": 639, 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{"text": "A central technique is to define a joint relation as a noisy-channel model , by composing a joint relation with a cascade of one or more conditional relations as in Fig. 1 ( Pereira and Riley , 1997 ; Knight and Graehl , 1998 ) .", "citing_paper_id": "P02-1001", "cited_paper_id": "External_876", "citing_paper_year": 2002, "cited_paper_year": 1997, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "speech recognition by composition of weighted finite automata", "cited_author_ids": ["Fernando C N Pereira", "Michael Riley"], "citing_author_ids": null, "extended_context": "We offer a theorem that highlights the broad applicability of these modeling techniques .4 If f ( input , output ) is a weighted regular relation , then the following statements are equivalent : ( 1 ) f is a joint probabilistic relation ; ( 2 ) f can be computed by a Markovian FST that halts with probability 1 ; ( 3 ) f can be expressed as a probabilistic regexp , i.e. , a regexp built up from atomic expressions a : b ( for a E E U -LCB- E -RCB- , b E A U -LCB- E -RCB- ) using concatenation , probabilistic union + p , and probabilistic closure * p. For defining conditional relations , a good regexp language is unknown to us , but they can be defined in several other ways : ( 1 ) via FSTs as in Fig. 1c , ( 2 ) by compilation of weighted rewrite rules ( Mohri and Sproat , 1996 ) , ( 3 ) by compilation of decision trees ( Sproat and Riley , 1996 ) , ( 4 ) as a relation that performs contextual left-to-right replacement of input substrings by a smaller conditional relation ( Gerdemann and van Noord , 1999 ) ,5 ( 5 ) by conditionalization of a joint relation as discussed below . A central technique is to define a joint relation as a noisy-channel model , by composing a joint relation with a cascade of one or more conditional relations as in Fig. 1 ( Pereira and Riley , 1997 ; Knight and Graehl , 1998 ) . The general form is illustrated by 3Conceptually , the parameters represent the probabilities of reading another a ( A ) ; reading another b ( ν ) ; transducing b to p rather than q ( µ ) ; starting to transduce p to a rather than x ( p ) .", "section_number": 2, "section_title": null, "intent": "Background", "cite_marker_offset": [174, 198], "sents_before": [[{"index": 1, "word": "A", "lemma": "a", "after": " ", "pos": "DT", "characterOffsetEnd": 1482, "segment_span": [0, 14], "characterOffsetBegin": 1481, "originalText": "A", "ArgType": null, "before": " "}, {"index": 2, "word": "central", "lemma": "central", "after": " ", "pos": "JJ", "characterOffsetEnd": 1490, "segment_span": [0, 14], "characterOffsetBegin": 1483, "originalText": "central", "ArgType": null, "before": " "}, {"index": 3, "word": "technique", "lemma": "technique", "after": " ", "pos": "NN", "characterOffsetEnd": 1500, "segment_span": [0, 14], "characterOffsetBegin": 1491, "originalText": "technique", "ArgType": 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by composing a joint relation with a cascade of one or more conditional relations as in Fig. 1 ( @@CITATION ; Knight and Graehl , 1998 ) .", "citation_id": "P02-1001_29", "citation_excerpt_index": 0, "section_name": "introduction"}
{"text": "We use the same set of binary features as in previous work on this dataset ( Pang et al. , 2002 ; Pang and Lee , 2004 ; Zaidan et al. , 2007 ) .", "citing_paper_id": "D08-1004", "cited_paper_id": "P04-1035", "citing_paper_year": 2008, "cited_paper_year": 2004, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "a sentimental education sentiment analysis using subjectivity summarization based on minimum cuts", "cited_author_ids": ["B Pang", "L Lee"], "citing_author_ids": null, "extended_context": "where ~ f ( · ) extracts a feature vector from a classified ~ document , θ are the corresponding weights of those features , and Zθ ( x ) def Ey u ( x , y ) is a normalizer . We use the same set of binary features as in previous work on this dataset ( Pang et al. , 2002 ; Pang and Lee , 2004 ; Zaidan et al. , 2007 ) . 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{"text": "Our classification framework , directly inspired by Blum and Chawla ( 2001 ) , integrates both perspectives , optimizing its labeling of speech segments based on both individual speech-segment classification scores and preferences for groups of speech segments to receive the same label .", "citing_paper_id": "W06-1639", "cited_paper_id": "External_7807", "citing_paper_year": 2006, "cited_paper_year": 2001, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "learning from labeled and unlabeled data using graph mincuts", "cited_author_ids": ["A Blum", "S Chawla"], "citing_author_ids": null, "extended_context": "As discussed in Section 1 , however , the conversational nature of our data implies the existence of various relationships that can be exploited to improve cumulative classification accuracy for speech segments belonging to the same debate . Our classification framework , directly inspired by Blum and Chawla ( 2001 ) , integrates both perspectives , optimizing its labeling of speech segments based on both individual speech-segment classification scores and preferences for groups of speech segments to receive the same label . In this section , we discuss the specific classification framework that we adopt and the set of mechanisms that we propose for modeling specific types of relationships .", "section_number": 4, "section_title": null, "intent": "Uses", "cite_marker_offset": [52, 76], "sents_before": [[{"index": 1, "word": "Our", "lemma": "we", "after": " ", "pos": "PRP$", "characterOffsetEnd": 426, "segment_span": [0, 18], "characterOffsetBegin": 423, "originalText": "Our", "ArgType": null, "before": " "}, {"index": 2, "word": "classification", "lemma": "classification", "after": " ", "pos": "NN", "characterOffsetEnd": 441, "segment_span": [0, 18], "characterOffsetBegin": 427, "originalText": "classification", "ArgType": null, "before": " "}, {"index": 3, "word": "framework", "lemma": "framework", "after": "", "pos": "NN", "characterOffsetEnd": 451, "segment_span": [0, 18], "characterOffsetBegin": 442, "originalText": "framework", "ArgType": "subj", "before": " "}, {"index": 4, "word": ",", "lemma": ",", 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{"text": "As for work on Arabic ( MSA ) , results have been reported on the PATB ( Kulick , Gabbard , and Marcus 2006 ; Diab 2007 ; Green and Manning 2010 ) , the Prague Dependency Treebank ( PADT ) ( Buchholz and Marsi 2006 ; Nivre 2008 ) and the CATiB ( Habash and Roth 2009 ) .", "citing_paper_id": "J13-1008", "cited_paper_id": "C10-1045", "citing_paper_year": 2013, "cited_paper_year": 2010, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "better arabic parsing baselines evaluations and analysis", "cited_author_ids": ["Spence Green", "Christopher D Manning"], "citing_author_ids": null, "extended_context": "Looking at Hebrew , a Semitic language related to Arabic , Tsarfaty and Sima'an ( 2007 ) report that extending POS and phrase structure tags with definiteness information helps unlexicalized PCFG parsing . As for work on Arabic ( MSA ) , results have been reported on the PATB ( Kulick , Gabbard , and Marcus 2006 ; Diab 2007 ; Green and Manning 2010 ) , the Prague Dependency Treebank ( PADT ) ( Buchholz and Marsi 2006 ; Nivre 2008 ) and the CATiB ( Habash and Roth 2009 ) . 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{"text": "For instance , Palmer and Hearst ( 1997 ) report that the SATZ system ( decision tree variant ) was trained on a set of about 800 labeled periods , which corresponds to a corpus of about 16,000 words .", "citing_paper_id": "J02-3002", "cited_paper_id": "J97-2002", "citing_paper_year": 2002, "cited_paper_year": 1997, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "adaptive multilingual sentence boundary disambiguation", "cited_author_ids": ["David D Palmer", "Marti A Hearst"], "citing_author_ids": null, "extended_context": "Although some SBD systems can be trained on relatively small sets of labeled examples , their performance in such cases is somewhat lower than their optimal performance . For instance , Palmer and Hearst ( 1997 ) report that the SATZ system ( decision tree variant ) was trained on a set of about 800 labeled periods , which corresponds to a corpus of about 16,000 words . 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{"text": "One possible direction is to consider linguistically motivated approaches , such as the extraction of syntactic phrase tables as proposed by ( Yamada and Knight , 2001 ) .", "citing_paper_id": "P11-1134", "cited_paper_id": "P01-1067", "citing_paper_year": 2011, "cited_paper_year": 2001, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "a syntaxbased statistical translation model", "cited_author_ids": ["Kenji Yamada", "Kevin Knight"], "citing_author_ids": null, "extended_context": "On one side , we plan to explore alternative ways to build phrase and paraphrase tables . One possible direction is to consider linguistically motivated approaches , such as the extraction of syntactic phrase tables as proposed by ( Yamada and Knight , 2001 ) . Another interesting direction is to investigate the potential of paraphrase patterns ( i.e. patterns including partof-speech slots ) , extracted from bilingual parallel corpora with the method proposed by ( Zhao et al. , 2009 ) .", "section_number": 5, "section_title": null, "intent": "Future", "cite_marker_offset": [143, 167], "sents_before": [[{"index": 1, "word": "One", "lemma": "one", "after": " ", "pos": "CD", "characterOffsetEnd": 1782, "segment_span": [0, 28], "characterOffsetBegin": 1779, "originalText": "One", "ArgType": null, "before": " "}, {"index": 2, "word": "possible", "lemma": "possible", "after": " ", "pos": "JJ", "characterOffsetEnd": 1791, "segment_span": [0, 28], "characterOffsetBegin": 1783, "originalText": "possible", "ArgType": null, "before": " "}, {"index": 3, "word": "direction", "lemma": "direction", "after": " ", "pos": "NN", "characterOffsetEnd": 1801, "segment_span": [0, 28], "characterOffsetBegin": 1792, "originalText": "direction", "ArgType": "subj", 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{"text": "Later works , such as Atallah et al. ( 2001a ) , Bolshakov ( 2004 ) , Taskiran et al. ( 2006 ) and Topkara et al. ( 2006b ) , further made use of part-ofspeech taggers and electronic dictionaries , such as WordNet and VerbNet , to increase the robustness of the method .", "citing_paper_id": "N10-1084", "cited_paper_id": "External_64566", "citing_paper_year": 2010, "cited_paper_year": 2004, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "a method of linguistic steganography based on coladdressallyverified synonym", "cited_author_ids": ["Igor A Bolshakov"], "citing_author_ids": null, "extended_context": "The first lexical substitution method was proposed by Chapman and Davida ( 1997 ) . Later works , such as Atallah et al. ( 2001a ) , Bolshakov ( 2004 ) , Taskiran et al. ( 2006 ) and Topkara et al. ( 2006b ) , further made use of part-ofspeech taggers and electronic dictionaries , such as WordNet and VerbNet , to increase the robustness of the method . Taskiran et al. ( 2006 ) attempt to use context by prioritizing the alternatives using an ngram language model ; that is , rather than randomly choose an option from the synonym set , the system relies on the language model to select the synonym .", "section_number": 3, "section_title": null, "intent": "Background", "cite_marker_offset": [49, 67], "sents_before": [[{"index": 1, "word": "Later", "lemma": "later", "after": " ", "pos": "RB", "characterOffsetEnd": 209, "segment_span": [0, 47], "characterOffsetBegin": 204, "originalText": "Later", "ArgType": null, "before": " "}, {"index": 2, "word": "works", "characterOffsetEnd": 215, "after": "", "pos": "VBZ", "is_root": true, "lemma": "work", "segment_span": [0, 47], "tense": "Z", "characterOffsetBegin": 210, "originalText": "works", "ArgType": null, "before": " "}, {"index": 3, "word": ",", "lemma": ",", "after": " ", "pos": ",", "characterOffsetEnd": 216, "segment_span": [0, 47], "characterOffsetBegin": 215, "originalText": ",", "ArgType": null, 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( 2001a ) , @@CITATION , Taskiran et al. ( 2006 ) and Topkara et al. ( 2006b ) , further made use of part-ofspeech taggers and electronic dictionaries , such as WordNet and VerbNet , to increase the robustness of the method .", "citation_id": "N10-1084_8", "citation_excerpt_index": 0, "section_name": "related work"}
{"text": "A number of speech understanding systems have been developed during the past fifteen years ( Barnett et al. 1980 , Dixon and Martin 1979 , Erman et al. 1980 , Haton and Pierrel 1976 , Lea 1980 , Lowerre and Reddy 1980 , Medress 1980 , Reddy 1976 , Walker 1978 , and Wolf and Woods 1980 ) .", "citing_paper_id": "J86-1002", "cited_paper_id": "External_33232", "citing_paper_year": 1986, "cited_paper_year": 1976, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "organization and operation of a connected speech understanding system at lexical syntactic and semantic levels", "cited_author_ids": ["J Haton", "J Pierrel"], "citing_author_ids": null, "extended_context": "A number of speech understanding systems have been developed during the past fifteen years ( Barnett et al. 1980 , Dixon and Martin 1979 , Erman et al. 1980 , Haton and Pierrel 1976 , Lea 1980 , Lowerre and Reddy 1980 , Medress 1980 , Reddy 1976 , Walker 1978 , and Wolf and Woods 1980 ) . 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{"text": "The bottom panel of table 1 lists the results for the chosen lexicalized model ( SSN-Freq > 200 ) and five recent statistical parsers ( Ratnaparkhi , 1999 ; Collins , 1999 ; Charniak , 2000 ; Collins , 2000 ; Bod , 2001 ) .", "citing_paper_id": "E03-1002", "cited_paper_id": "External_63", "citing_paper_year": 2003, "cited_paper_year": 2000, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "discriminative reranking for natural language parsing", "cited_author_ids": ["Michael Collins"], "citing_author_ids": null, "extended_context": "The Tags model also does much better than the only other broad coverage neural network parser ( Costa et al. , 2001 ) . The bottom panel of table 1 lists the results for the chosen lexicalized model ( SSN-Freq > 200 ) and five recent statistical parsers ( Ratnaparkhi , 1999 ; Collins , 1999 ; Charniak , 2000 ; Collins , 2000 ; Bod , 2001 ) . 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{"text": "The basic Python reflection has already been implemented and used for large scale experiments with POS tagging , using pyMPI ( a message passing interface library for Python ) to coordinate experiments across a cluster of over 100 machines ( Curran and Clark , 2003 ; Clark et al. , 2003 ) .", "citing_paper_id": "W03-0806", "cited_paper_id": "E03-1071", "citing_paper_year": 2003, "cited_paper_year": 2003, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "investigating gis and smoothing for maximum entropy taggers", "cited_author_ids": ["James R Curran", "Stephen Clark"], "citing_author_ids": null, "extended_context": "Finally , since Python can produce stand-alone executables directly , it will be possible to create distributable code that does not require the entire infrastructure or Python interpreter to be installed . The basic Python reflection has already been implemented and used for large scale experiments with POS tagging , using pyMPI ( a message passing interface library for Python ) to coordinate experiments across a cluster of over 100 machines ( Curran and Clark , 2003 ; Clark et al. , 2003 ) . An example of using the Python tagger interface is shown in Figure 1 .", "section_number": 8, "section_title": null, "intent": "Background", "cite_marker_offset": [242, 265], "sents_before": [[{"index": 1, "word": "The", "lemma": "the", "after": " ", "pos": "DT", "characterOffsetEnd": 1319, "segment_span": [0, 18], "characterOffsetBegin": 1316, "originalText": "The", "ArgType": null, "before": " "}, {"index": 2, "word": "basic", "lemma": "basic", "after": " ", "pos": "JJ", "characterOffsetEnd": 1325, "segment_span": [0, 18], "characterOffsetBegin": 1320, "originalText": "basic", "ArgType": null, "before": " "}, {"index": 3, "word": "Python", "lemma": "Python", "after": " ", "pos": "NNP", "characterOffsetEnd": 1332, "segment_span": [0, 18], "characterOffsetBegin": 1326, "originalText": "Python", "ArgType": null, "before": " "}, {"index": 4, "word": "reflection", "lemma": "reflection", "after": " ", "pos": "NN", "characterOffsetEnd": 1343, "segment_span": [0, 18], "characterOffsetBegin": 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"cleaned_cite_text": "This imbalance foils thresholding strategies , clever as they might be ( Gale & Church , 1991 ; Wu & Xia , 1994 ; @@CITATION ) .", "citation_id": "P97-1063_9", "citation_excerpt_index": 0, "section_name": null}
{"text": "Training was done on the Penn Treebank ( Marcus et al. , 1993 ) Wall Street Journal data , sections 02-21 .", "citing_paper_id": "W01-0706", "cited_paper_id": "J93-2004", "citing_paper_year": 2001, "cited_paper_year": 1993, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "building a large annotated corpus of english the penn treebank", "cited_author_ids": ["M P Marcus", "B Santorini", "M Marcinkiewicz"], "citing_author_ids": null, "extended_context": "Training was done on the Penn Treebank ( Marcus et al. , 1993 ) Wall Street Journal data , sections 02-21 . 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{"text": "We performed Latent Semantic Analysis ( LSA ) over Wikipedia using the jLSI tool ( Giuliano , 2007 ) to measure the relatedness between words in the dataset .", "citing_paper_id": "P11-1134", "cited_paper_id": "External_43455", "citing_paper_year": 2011, "cited_paper_year": 2007, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "jlsi a tool for latent semantic indexing software available at httptccitcitresearchtextectoolsresourcesjlsihtml", "cited_author_ids": ["Claudio Giuliano"], "citing_author_ids": null, "extended_context": "Wikipedia ( WIKI ) . We performed Latent Semantic Analysis ( LSA ) over Wikipedia using the jLSI tool ( Giuliano , 2007 ) to measure the relatedness between words in the dataset . 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{"text": "For example , our previous work ( Nakov and Ng , 2009 ; Nakov and Ng , 2012 ) experimented with various techniques for combining a small bi-text for a resource-poor language ( Indonesian or Spanish , pretending that Spanish is resource-poor ) with a much larger bi-text for a related resource-rich language ( Malay or Portuguese ) ; the target language of all bi-texts was English .", "citing_paper_id": "D12-1027", "cited_paper_id": "D09-1141", "citing_paper_year": 2012, "cited_paper_year": 2009, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "improved statistical machine translation for resourcepoor languages using related resourcerich languages", "cited_author_ids": ["Preslav Nakov", "Hwee Tou Ng"], "citing_author_ids": null, "extended_context": "A third relevant line of research is on reusing bitexts between related languages without or with very little adaptation , which works well for very closely related languages . For example , our previous work ( Nakov and Ng , 2009 ; Nakov and Ng , 2012 ) experimented with various techniques for combining a small bi-text for a resource-poor language ( Indonesian or Spanish , pretending that Spanish is resource-poor ) with a much larger bi-text for a related resource-rich language ( Malay or Portuguese ) ; the target language of all bi-texts was English . However , our previous work did not attempt language adaptation , except for very simple transliteration for Portuguese -- Spanish that ignored context entirely ; since it could not substitute one word for a completely different word , it did not help much for Malay -- Indonesian , which use unified spelling .", "section_number": 3, "section_title": null, "intent": "CompareOrContrast", "cite_marker_offset": [34, 53], "sents_before": [[{"index": 1, "word": "For", "lemma": "for", "after": " ", "pos": "IN", "characterOffsetEnd": 821, "segment_span": [0, 59], "characterOffsetBegin": 818, "originalText": "For", "ArgType": null, "before": " "}, {"index": 2, "word": "example", "lemma": "example", "after": "", "pos": "NN", "characterOffsetEnd": 829, "segment_span": [0, 59], "characterOffsetBegin": 822, "originalText": "example", "ArgType": null, "before": " "}, {"index": 3, "word": ",", "lemma": ",", "after": " ", "pos": ",", "characterOffsetEnd": 830, "segment_span": [0, 59], 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techniques for combining a small bi-text for a resource-poor language ( Indonesian or Spanish , pretending that Spanish is resource-poor ) with a much larger bi-text for a related resource-rich language ( Malay or Portuguese ) ; the target language of all bi-texts was English .", "citation_id": "D12-1027_11", "citation_excerpt_index": 0, "section_name": "related work"}
{"text": "Various approaches for computing semantic relatedness of words or concepts have been proposed , e.g. dictionary-based ( Lesk , 1986 ) , ontology-based ( Wu and Palmer , 1994 ; Leacock and Chodorow , 1998 ) , information-based ( Resnik , 1995 ; Jiang and Conrath , 1997 ) or distributional ( Weeds and Weir , 2005 ) .", "citing_paper_id": "W06-1104", "cited_paper_id": "External_1645", "citing_paper_year": 2006, "cited_paper_year": 1986, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "automatic sense disambiguation using machine readable dictionaries how to tell a pine cone from an ice cream cone", "cited_author_ids": ["Michael Lesk"], "citing_author_ids": null, "extended_context": "Various approaches for computing semantic relatedness of words or concepts have been proposed , e.g. dictionary-based ( Lesk , 1986 ) , ontology-based ( Wu and Palmer , 1994 ; Leacock and Chodorow , 1998 ) , information-based ( Resnik , 1995 ; Jiang and Conrath , 1997 ) or distributional ( Weeds and Weir , 2005 ) . The knowledge sources used for computing relatedness can be as different as dictionaries , ontologies or large corpora .", "section_number": 3, "section_title": null, "intent": "Background", "cite_marker_offset": [120, 131], "sents_before": [[{"index": 1, "word": "Various", "lemma": "various", "after": " ", "pos": "JJ", "characterOffsetEnd": 7, "segment_span": [0, 58], "characterOffsetBegin": 0, "originalText": "Various", "ArgType": null, "before": ""}, {"index": 2, "word": "approaches", "lemma": "approach", "after": " ", "pos": "NNS", "characterOffsetEnd": 18, "segment_span": [0, 58], "characterOffsetBegin": 8, "originalText": "approaches", "ArgType": null, "before": " "}, {"index": 3, "word": "for", "lemma": "for", "after": " ", "pos": "IN", "characterOffsetEnd": 22, "segment_span": [0, 58], "characterOffsetBegin": 19, "originalText": "for", "ArgType": null, "before": " "}, {"index": 4, "word": "computing", "lemma": "compute", "after": " ", "pos": "VBG", "characterOffsetEnd": 32, 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{"text": "Another line of research approaches grounded language knowledge by augmenting distributional approaches of word meaning with perceptual information ( Andrews et al. , 2009 ; Steyvers , 2010 ; Feng and Lapata , 2010b ; Bruni et al. , 2011 ; Silberer and Lapata , 2012 ; Johns and Jones , 2012 ; Bruni et al. , 2012a ; Bruni et al. , 2012b ; Silberer et al. , 2013 ) .", "citing_paper_id": "D13-1115", "cited_paper_id": "P12-1015", "citing_paper_year": 2013, "cited_paper_year": 2012, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "distributional semantics in technicolor", "cited_author_ids": ["Elia Bruni", "Gemma Boleda", "Marco Baroni", "NamKhanh Tran"], "citing_author_ids": null, "extended_context": "Some efforts have tackled tasks such as automatic image caption generation ( Feng and Lapata , 2010a ; Ordonez et al. , 2011 ) , text illustration ( Joshi et al. , 2006 ) , or automatic location identification of Twitter users ( Eisenstein et al. , 2010 ; Wing and Baldridge , 2011 ; Roller et al. , 2012 ) . Another line of research approaches grounded language knowledge by augmenting distributional approaches of word meaning with perceptual information ( Andrews et al. , 2009 ; Steyvers , 2010 ; Feng and Lapata , 2010b ; Bruni et al. , 2011 ; Silberer and Lapata , 2012 ; Johns and Jones , 2012 ; Bruni et al. , 2012a ; Bruni et al. , 2012b ; Silberer et al. , 2013 ) . Although these approaches have differed in model definition , the general goal in this line of research has been to enhance word meaning with perceptual information in order to address one of the most common criticisms of distributional semantics : that the `` meaning of words is entirely given by other words '' ( Bruni et al. , 2012b ) .", "section_number": 2, "section_title": null, "intent": "Background", "cite_marker_offset": [294, 313], "sents_before": [[{"index": 1, "word": "Another", "lemma": "another", "after": " ", "pos": "DT", "characterOffsetEnd": 1176, "segment_span": [0, 8], "characterOffsetBegin": 1169, "originalText": "Another", "ArgType": null, "before": " "}, {"index": 2, "word": "line", "lemma": "line", "after": " ", "pos": "NN", "characterOffsetEnd": 1181, "segment_span": [0, 8], "characterOffsetBegin": 1177, "originalText": "line", "ArgType": "subj", "before": " "}, {"index": 3, "word": "of", "lemma": "of", "after": " ", "pos": "IN", "characterOffsetEnd": 1184, 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{"text": "Gurevych ( 2005 ) replicated the experiment of Rubenstein and Goodenough with the original 65 word pairs translated into German .", "citing_paper_id": "W06-1104", "cited_paper_id": "I05-1067", "citing_paper_year": 2006, "cited_paper_year": 2005, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "using the structure of a conceptual network in computing semantic relatedness", "cited_author_ids": ["Iryna Gurevych"], "citing_author_ids": null, "extended_context": "Furthermore , semantic relatedness is an intuitive concept and being forced to assign fine-grained continuous values is felt to overstrain the test subjects . Gurevych ( 2005 ) replicated the experiment of Rubenstein and Goodenough with the original 65 word pairs translated into German . 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{"text": "One approach to this more general problem , taken by the ` Nitrogen ' generator ( Langkilde and Knight , 1998a ; Langkilde and Knight , 1998b ) , takes advantage of standard statistical techniques by generating a lattice of all possible strings given a semantic representation as input and selecting the most likely output using a bigram language model .", "citing_paper_id": "P00-1012", "cited_paper_id": "External_5515", "citing_paper_year": 2000, "cited_paper_year": 1998, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "generation that exploits corpusbased statistical knowledge", "cited_author_ids": ["Irene Langkilde", "Kevin Knight"], "citing_author_ids": null, "extended_context": "The problem of generating ordered sequences of adjectives is an instance of the more general problem of selecting among a number of possible outputs from a natural language generation system . One approach to this more general problem , taken by the ` Nitrogen ' generator ( Langkilde and Knight , 1998a ; Langkilde and Knight , 1998b ) , takes advantage of standard statistical techniques by generating a lattice of all possible strings given a semantic representation as input and selecting the most likely output using a bigram language model . 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{"text": "where mk is one mention in entity e , and the basic model building block PL ( L = 1 | e , mk , m ) is an exponential or maximum entropy model ( Berger et al. , 1996 ) .", "citing_paper_id": "W05-0709", "cited_paper_id": "External_3692", "citing_paper_year": 2005, "cited_paper_year": 1996, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "a maximum entropy approach to natural language processing", "cited_author_ids": ["A Berger", "S Della Pietra", "V Della Pietra"], "citing_author_ids": null, "extended_context": "2Thus , the difference to token n-grams is that the tokens of different type are removed from the streams , before the features are created . where mk is one mention in entity e , and the basic model building block PL ( L = 1 | e , mk , m ) is an exponential or maximum entropy model ( Berger et al. , 1996 ) . 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{"text": "13 We also employed sequence-based measures using the ROUGE tool set ( Lin and Hovy 2003 ) , with similar results to those obtained with the word-by-word measures .", "citing_paper_id": "J09-4010", "cited_paper_id": "N03-1020", "citing_paper_year": 2009, "cited_paper_year": 2003, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "automatic evaluation of summaries using ngram cooccurrence statistics", "cited_author_ids": ["C Y Lin", "E H Hovy"], "citing_author_ids": null, "extended_context": "Table 5 presents the coverage and unique/best coverage of each method ( the percentage of queries covered only by this method or for which this method produces a better reply than other methods ) , and the average and standard deviation of the precision and F-score obtained by each method ( calculated over the requests that are covered ) . 13 We also employed sequence-based measures using the ROUGE tool set ( Lin and Hovy 2003 ) , with similar results to those obtained with the word-by-word measures . 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"characterOffsetEnd": 65, "segment_span": [0, 13], "characterOffsetBegin": 58, "originalText": "product", "ArgType": "dobj", "before": ""}]], "cleaned_cite_text": "13 We also employed sequence-based measures using the ROUGE tool set ( @@CITATION ) , with similar results to those obtained with the word-by-word measures .", "citation_id": "J09-4010_29", "citation_excerpt_index": 0, "section_name": "method"}
{"text": "Second , using continuous distributions allows us to leverage a variety of tools ( e.g. , LDA ) that have been shown to be successful in other fields , such as speech recognition ( Evermann et al. , 2004 ) .", "citing_paper_id": "W06-3309", "cited_paper_id": "External_74942", "citing_paper_year": 2006, "cited_paper_year": 2004, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "cuhtk conversational telephone speech transcription system", "cited_author_ids": ["Gunnar Evermann", "H Y Chan", "Mark J F Gales", "Thomas Hain", "Xunying Liu", "David Mrva", "Lan Wang", "Phil Woodland"], "citing_author_ids": null, "extended_context": "This is not possible when modeling word sequences , where only the probability of a sentence is actually used in the HMM training . Second , using continuous distributions allows us to leverage a variety of tools ( e.g. , LDA ) that have been shown to be successful in other fields , such as speech recognition ( Evermann et al. , 2004 ) . Table 2 ( b ) represents the closest head-to-head comparison between our generative approach ( HMM with LDA ) and state-of-the-art results reported by M&S using SVMs .", "section_number": 5, "section_title": null, "intent": "Background", "cite_marker_offset": [181, 203], "sents_before": [[{"index": 1, "word": "Second", "lemma": "second", "after": "", "pos": "RB", "characterOffsetEnd": 547, "segment_span": [0, 40], "characterOffsetBegin": 541, "originalText": "Second", "ArgType": null, "before": " "}, {"index": 2, "word": ",", "lemma": ",", "after": " ", "pos": ",", "characterOffsetEnd": 548, "segment_span": [0, 40], "characterOffsetBegin": 547, "originalText": ",", "ArgType": null, "before": ""}, {"index": 3, "word": "using", "lemma": "use", "after": " ", "pos": "VBG", "characterOffsetEnd": 554, "segment_span": [0, 40], "characterOffsetBegin": 549, "originalText": "using", "ArgType": null, "before": " "}, {"index": 4, "word": "continuous", "lemma": "continuous", "after": " ", "pos": 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{"text": "In this section , we validate the contribution of key tag sets and morphological features -- and combinations thereof -- using a different parser : the Easy-First Parser ( Goldberg and Elhadad 2010 ) .", "citing_paper_id": "J13-1008", "cited_paper_id": "N10-1115", "citing_paper_year": 2013, "cited_paper_year": 2010, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "an efficient algorithm for easyfirst nondirectional dependency parsing", "cited_author_ids": ["Yoav Goldberg", "Michael Elhadad"], "citing_author_ids": null, "extended_context": "In this section , we validate the contribution of key tag sets and morphological features -- and combinations thereof -- using a different parser : the Easy-First Parser ( Goldberg and Elhadad 2010 ) . 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{"text": "The typical solution to the redundancy problem is to group verbs according to their argument realization patterns ( Levin , 1993 ) , possibly arranged in an inheritance hierarchy .", "citing_paper_id": "N04-2004", "cited_paper_id": "External_164", "citing_paper_year": 2004, "cited_paper_year": 1993, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "english verb classes and alternations a preliminary investigation", "cited_author_ids": ["Beth Levin"], "citing_author_ids": null, "extended_context": "The major drawback of this approach , however , is the tremendous amount of redundancy in the lexicon -- for example , the class of prototypical transitive verbs where the agent appears as the subject and the theme as the direct object must all duplicate this pattern . The typical solution to the redundancy problem is to group verbs according to their argument realization patterns ( Levin , 1993 ) , possibly arranged in an inheritance hierarchy . The argument structure and syntax-tosemantics mapping would then only need to be specified once for each verb class .", "section_number": 2, "section_title": null, "intent": "CompareOrContrast", "cite_marker_offset": [116, 128], "sents_before": [[{"index": 1, "word": "The", "lemma": "the", "after": " ", "pos": "DT", "characterOffsetEnd": 437, "segment_span": [0, 29], "characterOffsetBegin": 434, "originalText": "The", "ArgType": null, "before": " "}, {"index": 2, "word": "typical", "lemma": "typical", "after": " ", "pos": "JJ", "characterOffsetEnd": 445, "segment_span": [0, 29], "characterOffsetBegin": 438, "originalText": "typical", "ArgType": null, "before": " "}, {"index": 3, "word": "solution", "lemma": "solution", "after": " ", "pos": "NN", "characterOffsetEnd": 454, "segment_span": [0, 29], "characterOffsetBegin": 446, "originalText": "solution", "ArgType": "subj", "before": " "}, {"index": 4, "word": "to", "lemma": "to", "after": " ", "pos": "TO", "characterOffsetEnd": 457, 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{"text": "Later , Hobbs ( 1979 , 1982 ) proposed a knowledge base in which information about language and the world would be encoded , and he emphasized the need for using `` salience '' in choosing facts from this knowledge base .", "citing_paper_id": "J91-2003", "cited_paper_id": "External_5163", "citing_paper_year": 1991, "cited_paper_year": 1979, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "coherence and coreferencequot", "cited_author_ids": ["J R Hobbs"], "citing_author_ids": null, "extended_context": "Adding selectional restrictions ( semantic feature information , Hobbs 1977 ) does not solve the problem , because isolated features offer only part of the background knowledge necessary for reference disambiguation . Later , Hobbs ( 1979 , 1982 ) proposed a knowledge base in which information about language and the world would be encoded , and he emphasized the need for using `` salience '' in choosing facts from this knowledge base . We will investigate the possibility that the structure of this knowledge base can actually resemble the structure of , for example , natural language dictionaries .", "section_number": 1, "section_title": null, "intent": "Background", "cite_marker_offset": [8, 20], "sents_before": [[{"index": 1, "word": "Later", "lemma": "later", "after": "", "pos": "RB", "characterOffsetEnd": 2141, "segment_span": [0, 25], "characterOffsetBegin": 2136, "originalText": "Later", "ArgType": null, "before": " "}, {"index": 2, "word": ",", "lemma": ",", "after": " ", "pos": ",", "characterOffsetEnd": 2142, "segment_span": [0, 25], "characterOffsetBegin": 2141, "originalText": ",", "ArgType": null, "before": ""}, {"index": 3, "word": "Hobbs", "lemma": "Hobbs", "after": " ", "pos": "NNP", "characterOffsetEnd": 2148, "segment_span": [0, 25], "characterOffsetBegin": 2143, "originalText": "Hobbs", "ArgType": "subj", "before": " "}, {"index": 4, "word": "(", "lemma": "-lrb-", "after": "", "pos": "-LRB-", 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{"text": "ASARES is presented in detail in ( Claveau et al. , 2003 ) .", "citing_paper_id": "W04-1805", "cited_paper_id": "External_44706", "citing_paper_year": 2004, "cited_paper_year": 2003, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "learning semantic lexicons from a partofspeech and semantically tagged corpus using inductive logic programming", "cited_author_ids": ["Vincent Claveau", "Pascale Sebillot", "Cecile Fabre", "Pierrette Bouillon"], "citing_author_ids": null, "extended_context": "The method used for the acquisition of N-V pairs relies mainly on ASARES , a pattern inference tool . ASARES is presented in detail in ( Claveau et al. , 2003 ) . 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{"text": "Opposition ( called `` adversative '' or `` contrary-to-expectation '' by Halliday and Hasan 1976 ; cfXXX also Quirk et al. 1972 , p. 672 ) .", "citing_paper_id": "J91-2003", "cited_paper_id": "External_504", "citing_paper_year": 1991, "cited_paper_year": 1976, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "cohesion in english", "cited_author_ids": ["M A K Halliday", "R Hasan"], "citing_author_ids": null, "extended_context": "1 . Opposition ( called `` adversative '' or `` contrary-to-expectation '' by Halliday and Hasan 1976 ; cfXXX also Quirk et al. 1972 , p. 672 ) . 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{"text": "A number of applications have relied on distributional analysis ( Harris , 1971 ) in order to build classes of semantically related terms .", "citing_paper_id": "W04-1805", "cited_paper_id": "External_95820", "citing_paper_year": 2004, "cited_paper_year": 1971, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "structures mathematiques du langage", "cited_author_ids": ["Zellig Harris"], "citing_author_ids": null, "extended_context": "A number of applications have relied on distributional analysis ( Harris , 1971 ) in order to build classes of semantically related terms . This approach , which uses words that appear in the context of terms to formulate hypotheses on their semantic relatedness ( Habert et al. , 1996 , for example ) , does not specify the relationship itself .", "section_number": 4, "section_title": null, "intent": "Background", "cite_marker_offset": [66, 79], "sents_before": [[{"index": 1, "word": "A", "lemma": "a", "after": " ", "pos": "DT", "characterOffsetEnd": 1, "segment_span": [0, 14], "characterOffsetBegin": 0, "originalText": "A", "ArgType": null, "before": ""}, {"index": 2, "word": "number", "lemma": "number", "after": " ", "pos": "NN", "characterOffsetEnd": 8, "segment_span": [0, 14], "characterOffsetBegin": 2, "originalText": "number", "ArgType": "subj", "before": " "}, {"index": 3, "word": "of", "lemma": "of", "after": " ", "pos": "IN", "characterOffsetEnd": 11, "segment_span": [0, 14], "characterOffsetBegin": 9, "originalText": "of", "ArgType": null, "before": " "}, {"index": 4, "word": "applications", "lemma": 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{"text": "Previous work with MaltParser in Russian , Turkish , and Hindi showed gains with CASE but not with agreement features ( Eryigit , Nivre , and Oflazer 2008 ; Nivre , Boguslavsky , and Iomdin 2008 ; Nivre 2009 ) .", "citing_paper_id": "J13-1008", "cited_paper_id": "External_4979", "citing_paper_year": 2013, "cited_paper_year": 2009, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "parsing indian languages with maltparser", "cited_author_ids": ["Joakim Nivre"], "citing_author_ids": null, "extended_context": "We go beyond previous work , however , and explore additional lexical and inflectional features . Previous work with MaltParser in Russian , Turkish , and Hindi showed gains with CASE but not with agreement features ( Eryigit , Nivre , and Oflazer 2008 ; Nivre , Boguslavsky , and Iomdin 2008 ; Nivre 2009 ) . 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{"text": "Consider , for example , the lexical rule in Figure 2 , which encodes a passive lexical rule like the one presented by Pollard and Sag ( 1987 , 215 ) in terms of the setup of Pollard and Sag ( 1994 , ch .", "citing_paper_id": "J97-4003", "cited_paper_id": "External_24531", "citing_paper_year": 1997, "cited_paper_year": 1987, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "of csli lecture notes center for the study of language and information", "cited_author_ids": ["Carl Pollard", "Ivan Sag"], "citing_author_ids": null, "extended_context": "written as fully specified relations between words , rather , only what is supposed to be changed is specified . Consider , for example , the lexical rule in Figure 2 , which encodes a passive lexical rule like the one presented by Pollard and Sag ( 1987 , 215 ) in terms of the setup of Pollard and Sag ( 1994 , ch . 9 ) .", "section_number": 2, "section_title": null, "intent": "CompareOrContrast", "cite_marker_offset": [119, 141], "sents_before": [[{"index": 1, "word": "Consider", "characterOffsetEnd": 148, "after": "", "pos": "VB", "is_root": true, "lemma": "consider", "segment_span": [0, 12], "tense": "B", "characterOffsetBegin": 140, "originalText": "Consider", "ArgType": null, "before": " "}, {"index": 2, "word": ",", "lemma": ",", "after": " ", "pos": ",", "characterOffsetEnd": 149, "segment_span": [0, 12], "characterOffsetBegin": 148, "originalText": ",", "ArgType": null, "before": ""}, {"index": 3, "word": "for", "lemma": "for", "after": " ", "pos": "IN", "characterOffsetEnd": 153, "segment_span": [0, 12], "characterOffsetBegin": 150, "originalText": "for", "ArgType": null, "before": " "}, 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{"text": "Two applications that , like help-desk , deal with question -- answer pairs are : summarization of e-mail threads ( Dalli , Xia , and Wilks 2004 ; Shrestha and McKeown 2004 ) , and answer extraction in FAQs ( Frequently Asked Questions ) ( Berger and Mittal 2000 ;", "citing_paper_id": "J09-4010", "cited_paper_id": "C04-1128", "citing_paper_year": 2009, "cited_paper_year": 2004, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "detection of questionanswer pairs in email conversations", "cited_author_ids": ["L Shrestha", "K R McKeown"], "citing_author_ids": null, "extended_context": "With respect to these systems , the contribution of our work lies in the consideration of different kinds of corpus-based approaches ( namely , retrieval and prediction ) applied at different levels of granularity ( namely , document and sentence ) . Two applications that , like help-desk , deal with question -- answer pairs are : summarization of e-mail threads ( Dalli , Xia , and Wilks 2004 ; Shrestha and McKeown 2004 ) , and answer extraction in FAQs ( Frequently Asked Questions ) ( Berger and Mittal 2000 ; Berger et al. 2000 ; Jijkoun and de Rijke 2005 ; Soricut and Brill 2006 ) .", "section_number": 5, "section_title": null, "intent": "CompareOrContrast", "cite_marker_offset": [147, 172], "sents_before": [[{"index": 1, "word": "Two", "lemma": "two", "after": " ", "pos": "CD", "characterOffsetEnd": 3664, "segment_span": [0, 49], "characterOffsetBegin": 3661, "originalText": "Two", "ArgType": null, "before": " "}, {"index": 2, "word": "applications", "lemma": "application", "after": " ", "pos": "NNS", "characterOffsetEnd": 3677, "segment_span": [0, 49], "characterOffsetBegin": 3665, "originalText": "applications", "ArgType": null, "before": " "}, {"index": 3, "word": "that", "lemma": "that", "after": "", "pos": "IN", 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{"text": "The language grounding problem has received significant attention in recent years , owed in part to the wide availability of data sets ( e.g. Flickr , Von Ahn ( 2006 ) ) , computing power , improved computer vision models ( Oliva and Torralba , 2001 ; Lowe , 2004 ; Farhadi et al. , 2009 ; Parikh and Grauman , 2011 ) and neurological evidence of ties between the language , perceptual and motor systems in the brain ( Pulverm ¨ uller et al. , 2005 ; Tettamanti et al. , 2005 ; Aziz-Zadeh et al. , 2006 ) .", "citing_paper_id": "D13-1115", "cited_paper_id": "External_2129", "citing_paper_year": 2013, "cited_paper_year": 2009, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "describing objects by their attributes", "cited_author_ids": ["Ali Farhadi", "Ian Endres", "Derek Hoiem", "David Forsyth"], "citing_author_ids": null, "extended_context": "The language grounding problem has received significant attention in recent years , owed in part to the wide availability of data sets ( e.g. Flickr , Von Ahn ( 2006 ) ) , computing power , improved computer vision models ( Oliva and Torralba , 2001 ; Lowe , 2004 ; Farhadi et al. , 2009 ; Parikh and Grauman , 2011 ) and neurological evidence of ties between the language , perceptual and motor systems in the brain ( Pulverm ¨ uller et al. , 2005 ; Tettamanti et al. , 2005 ; Aziz-Zadeh et al. , 2006 ) . 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{"text": "In addition , we find that the Bayesian SCFG grammar can not even significantly outperform the heuristic SCFG grammar ( Blunsom et al. 2009 ) 5 .", "citing_paper_id": "Q13-1020", "cited_paper_id": "P09-1088", "citing_paper_year": 2013, "cited_paper_year": 2009, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "a gibbs sampler for phrasal synchronous grammar induction", "cited_author_ids": ["Phil Blunsom", "Trevor Cohn", "Chris Dyer", "Miles Osborne"], "citing_author_ids": null, "extended_context": "Thus , using STSG , we can build more specific U-trees for translation . In addition , we find that the Bayesian SCFG grammar can not even significantly outperform the heuristic SCFG grammar ( Blunsom et al. 2009 ) 5 . This would indicate that the SCFG-based derivation tree as by-product is also not such good for tree-based translation models .", "section_number": 4, "section_title": null, "intent": "CompareOrContrast", "cite_marker_offset": [120, 139], "sents_before": [[{"index": 1, "word": "In", "lemma": "in", "after": " ", "pos": "IN", "characterOffsetEnd": 1219, "segment_span": [0, 5], "characterOffsetBegin": 1217, "originalText": "In", "ArgType": null, "before": " "}, {"index": 2, "word": "addition", "lemma": "addition", "after": "", "pos": "NN", "characterOffsetEnd": 1228, "segment_span": [0, 5], "characterOffsetBegin": 1220, "originalText": "addition", "ArgType": null, "before": " "}, {"index": 3, "word": ",", "lemma": ",", "after": " ", "pos": ",", "characterOffsetEnd": 1229, "segment_span": [0, 5], "characterOffsetBegin": 1228, "originalText": ",", "ArgType": null, "before": ""}, {"index": 4, "word": "we", "lemma": "we", "after": " ", "pos": "PRP", "characterOffsetEnd": 1232, "segment_span": 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{"text": "Although the approach may have potential , the shifting of complex accounting into the unification algorithm is at variance with the findings of Kiefer et al. ( 1999 ) , who report large speed-ups from the elimination of disjunction processing during unification .", "citing_paper_id": "A00-2022", "cited_paper_id": "P99-1061", "citing_paper_year": 2000, "cited_paper_year": 1999, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "a bag of useful techniques for efficient and robust parsing", "cited_author_ids": ["B Kiefer", "H-U Krieger", "J Carroll", "R Malouf"], "citing_author_ids": null, "extended_context": "In related work , Miyao ( 1999 ) describes an approach to packing in which alternative feature structures are represented as packed , distributed disjunctions of feature structure fragments . Although the approach may have potential , the shifting of complex accounting into the unification algorithm is at variance with the findings of Kiefer et al. ( 1999 ) , who report large speed-ups from the elimination of disjunction processing during unification . Unfortunately , the reported evaluation measures and lack of discussion of parser control issues are insufficient to allow a precise comparison .", "section_number": 4, "section_title": null, "intent": "CompareOrContrast", "cite_marker_offset": [145, 167], "sents_before": [[{"index": 1, "word": "Although", "lemma": "although", "after": " ", "pos": "IN", "characterOffsetEnd": 849, "segment_span": [0, 6], "characterOffsetBegin": 841, "originalText": "Although", "ArgType": null, "before": " "}, {"index": 2, "word": "the", "lemma": "the", "after": " ", "pos": "DT", "characterOffsetEnd": 853, "segment_span": [0, 6], "characterOffsetBegin": 850, "originalText": "the", "ArgType": null, "before": " "}, {"index": 3, "word": "approach", "lemma": "approach", "after": " ", "pos": "NN", "characterOffsetEnd": 862, "segment_span": [0, 6], "characterOffsetBegin": 854, "originalText": "approach", "ArgType": "subj", "before": " "}, {"index": 4, "word": "may", "lemma": "may", "after": " ", "pos": "MD", 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{"text": "For the task of unsupervised dependency parsing , Smith and Eisner ( 2006 ) add a constraint of the form `` the average length of dependencies should be X '' to capture the locality of syntax ( at least half of the dependencies are between adjacent words ) , using a scheme they call structural annealing .", "citing_paper_id": "J10-3007", "cited_paper_id": "P06-1072", "citing_paper_year": 2010, "cited_paper_year": 2006, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "annealing structural bias in multilingual weighted grammar induction", "cited_author_ids": ["Noah A Smith", "Jason Eisner"], "citing_author_ids": null, "extended_context": "This encourages more transitions and hence shorter phrases . For the task of unsupervised dependency parsing , Smith and Eisner ( 2006 ) add a constraint of the form `` the average length of dependencies should be X '' to capture the locality of syntax ( at least half of the dependencies are between adjacent words ) , using a scheme they call structural annealing . They modify the model 's distribution over trees pe ( y ) by a penalty term as : pe ( y ) ∝ pe ( y ) e ( δ Ee ∈ y length ( e ) ) , where length ( e ) is the surface length of edge e .", "section_number": 6, "section_title": null, "intent": "Background", "cite_marker_offset": [50, 75], "sents_before": [[{"index": 1, "word": "For", "lemma": "for", "after": " ", "pos": "IN", "characterOffsetEnd": 575, "segment_span": [0, 49], "characterOffsetBegin": 572, "originalText": "For", "ArgType": null, "before": " "}, {"index": 2, "word": "the", "lemma": "the", "after": " ", "pos": "DT", "characterOffsetEnd": 579, "segment_span": [0, 49], "characterOffsetBegin": 576, "originalText": "the", "ArgType": null, "before": " "}, {"index": 3, "word": "task", "lemma": "task", "after": " ", "pos": "NN", "characterOffsetEnd": 584, "segment_span": [0, 49], "characterOffsetBegin": 580, "originalText": "task", "ArgType": null, "before": " "}, {"index": 4, "word": "of", "lemma": "of", "after": " ", "pos": "IN", 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{"text": "Second , in line with the findings of ( Mehdad et al. , 2010 ) , the results obtained over the MT-derived corpus are equal to those we achieve over the original RTE3 dataset ( i.e. 63.50 % ) .", "citing_paper_id": "P11-1134", "cited_paper_id": "N10-1146", "citing_paper_year": 2011, "cited_paper_year": 2010, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "syntacticsemantic structures for textual entailment recognition", "cited_author_ids": ["Yashar Mehdad", "Alessandro Moschitti", "Fabio Massimo Zanzotto"], "citing_author_ids": null, "extended_context": "This suggests that the noise introduced by incorrect translations can be tackled by increasing the coverage of the paraphrase table . Second , in line with the findings of ( Mehdad et al. , 2010 ) , the results obtained over the MT-derived corpus are equal to those we achieve over the original RTE3 dataset ( i.e. 63.50 % ) . 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{"text": "Therefore , inter-subject correlation is lower than the results obtained by Gurevych ( 2006 ) .", "citing_paper_id": "W06-1104", "cited_paper_id": "External_61155", "citing_paper_year": 2006, "cited_paper_year": 2006, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "computing semantic relatedness across parts of speech", "cited_author_ids": ["Iryna Gurevych"], "citing_author_ids": null, "extended_context": "Due to the corpusbased approach , many domain-specific concept pairs are introduced into the test set . Therefore , inter-subject correlation is lower than the results obtained by Gurevych ( 2006 ) . In our experiment , intra-subject correlation was r = .670 for the first and r = .623 for the second individual who repeated the experiment , yielding a summarized intra-subject correlation of r = .647 .", "section_number": 6, "section_title": null, "intent": "CompareOrContrast", "cite_marker_offset": [76, 93], "sents_before": [[{"index": 1, "word": "Therefore", "lemma": "therefore", "after": "", "pos": "RB", "characterOffsetEnd": 241, "segment_span": [0, 15], "characterOffsetBegin": 232, "originalText": "Therefore", "ArgType": null, "before": " "}, {"index": 2, "word": ",", "lemma": ",", "after": " ", "pos": ",", "characterOffsetEnd": 242, "segment_span": [0, 15], "characterOffsetBegin": 241, "originalText": ",", "ArgType": null, "before": ""}, {"index": 3, "word": "inter-subject", "lemma": "inter-subject", "after": " ", "pos": "JJ", "characterOffsetEnd": 256, "segment_span": [0, 15], "characterOffsetBegin": 243, "originalText": "inter-subject", "ArgType": null, "before": " "}, 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{"text": "There is a general consensus among theoretical linguists that the proper representation of verbal argument structure is event structure -- representations grounded in a theory of events that decompose semantic roles in terms of primitive predicates representing concepts such as causality and inchoativity ( Dowty , 1979 ; Jackendoff , 1983 ; Pustejovsky , 1991b ; Rappaport Hovav and Levin , 1998 ) .", "citing_paper_id": "N04-2004", "cited_paper_id": "External_3105", "citing_paper_year": 2004, "cited_paper_year": 1998, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "building verb meanings", "cited_author_ids": ["Malka Rappaport Hovav", "Beth Levin"], "citing_author_ids": null, "extended_context": "Fixed roles are too coarsegrained to account for certain semantic distinctions -- the only recourse , to expand the inventory of roles , comes with the price of increased complexity , e.g. , in the syntaxto-semantics mapping . There is a general consensus among theoretical linguists that the proper representation of verbal argument structure is event structure -- representations grounded in a theory of events that decompose semantic roles in terms of primitive predicates representing concepts such as causality and inchoativity ( Dowty , 1979 ; Jackendoff , 1983 ; Pustejovsky , 1991b ; Rappaport Hovav and Levin , 1998 ) . Consider the following example :", "section_number": 3, "section_title": null, "intent": "Background", "cite_marker_offset": [375, 397], "sents_before": [[{"index": 1, "word": "There", "lemma": "there", "after": " ", "pos": "EX", "characterOffsetEnd": 531, "segment_span": [0, 27], "characterOffsetBegin": 526, "originalText": "There", "ArgType": null, "before": " "}, {"index": 2, "word": "is", "characterOffsetEnd": 534, "after": " ", "pos": "VBZ", "is_root": true, "lemma": "be", "segment_span": [0, 27], "tense": "Z", "characterOffsetBegin": 532, "originalText": "is", "ArgType": "verb", "before": " "}, {"index": 3, "word": "a", "lemma": "a", "after": " ", "pos": "DT", "characterOffsetEnd": 536, "segment_span": [0, 27], "characterOffsetBegin": 535, "originalText": "a", "ArgType": null, "before": " "}, {"index": 4, "word": "general", "lemma": "general", "after": " ", "pos": "JJ", "characterOffsetEnd": 544, "segment_span": [0, 27], "characterOffsetBegin": 537, "originalText": "general", 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{"text": "The resulting training procedure is analogous to the one presented in ( Brown et al. , 1993 ) and ( Tillmann and Ney , 1997 ) .", "citing_paper_id": "D08-1039", "cited_paper_id": "W97-1014", "citing_paper_year": 2008, "cited_paper_year": 1997, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "word triggers and the em algorithm", "cited_author_ids": ["Christoph Tillmann", "Hermann Ney"], "citing_author_ids": null, "extended_context": "The function δ ( · , · ) denotes the Kronecker delta . The resulting training procedure is analogous to the one presented in ( Brown et al. , 1993 ) and ( Tillmann and Ney , 1997 ) . The next section presents variants of the basic unconstrained model by putting restrictions on the valid regions of triggers ( in-phrase vs. out-ofphrase ) and using alignments obtained from either GIZA + + training or forced alignments in order to reduce the model size and to incorporate knowledge already obtained in previous training steps .", "section_number": 4, "section_title": null, "intent": "CompareOrContrast", "cite_marker_offset": [100, 123], "sents_before": [[{"index": 1, "word": "The", "lemma": "the", "after": " ", "pos": "DT", "characterOffsetEnd": 53, "segment_span": [0, 26], "characterOffsetBegin": 50, "originalText": "The", "ArgType": null, "before": " "}, {"index": 2, "word": "resulting", "lemma": "result", "after": " ", "pos": "VBG", "characterOffsetEnd": 63, "segment_span": [0, 26], "characterOffsetBegin": 54, "originalText": "resulting", "ArgType": null, "before": " "}, {"index": 3, "word": "training", "lemma": "training", "after": " ", "pos": "NN", 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{"text": "successfully parses , or until a quitting criterion is reached , such as an upper bound on N. Whereas in the loosely coupled system the parser acts as a filter only on completed candidate solutions ( Zue et al. 1991 ) , the tightly coupled system allows the parser to discard partial theories that have no way of continuing .", "citing_paper_id": "J92-1004", "cited_paper_id": "External_36647", "citing_paper_year": 1992, "cited_paper_year": 1991, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "integration of speech recognition and natural language processing in the mit voyager systemquot", "cited_author_ids": ["V Zue", "J Glass", "D Goodine", "H Leung", "M Phillips", "J Polifroni", "S Seneff"], "citing_author_ids": null, "extended_context": "The recognizer can continue to propose hypotheses until one successfully parses , or until a quitting criterion is reached , such as an upper bound on N. 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{"text": "Much of the earlier work in anaphora resolution heavily exploited domain and linguistic knowledge ( Sidner 1979 ; Carter 1987 ; Rich and LuperFoy 1988 ; Carbonell and Brown 1988 ) , which was difficult both to represent and to process , and which required considerable human input .", "citing_paper_id": "J01-4001", "cited_paper_id": "External_21667", "citing_paper_year": 2001, "cited_paper_year": 1979, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "toward a computational theory of definite anaphora comprehension in english", "cited_author_ids": ["Candace Sidner"], "citing_author_ids": null, "extended_context": "Last , but not least , application-driven research in areas such as automatic abstracting and information extraction independently highlighted the importance of anaphora and coreference resolution , boosting research in this area . Much of the earlier work in anaphora resolution heavily exploited domain and linguistic knowledge ( Sidner 1979 ; Carter 1987 ; Rich and LuperFoy 1988 ; Carbonell and Brown 1988 ) , which was difficult both to represent and to process , and which required considerable human input . However , the pressing need for the development of robust and inexpensive solutions to meet the demands of practical NLP systems encouraged many researchers to move away from extensive domain and linguistic knowledge and to embark instead upon knowledge-poor anaphora resolution strategies .", "section_number": 0, "section_title": null, "intent": "Background", "cite_marker_offset": [100, 111], "sents_before": [[{"index": 1, "word": "Much", "lemma": "much", "after": " ", "pos": "JJ", "characterOffsetEnd": 1200, "segment_span": [0, 32], "characterOffsetBegin": 1196, "originalText": "Much", "ArgType": "subj", "before": " "}, {"index": 2, "word": "of", "lemma": "of", "after": " ", "pos": "IN", "characterOffsetEnd": 1203, "segment_span": [0, 32], "characterOffsetBegin": 1201, "originalText": "of", "ArgType": null, "before": " "}, {"index": 3, "word": "the", "lemma": "the", "after": " ", "pos": "DT", "characterOffsetEnd": 1207, "segment_span": [0, 32], "characterOffsetBegin": 1204, 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{"text": "The Praat tool was used ( Boersma and Weenink , 2009 ) .", "citing_paper_id": "P10-2059", "cited_paper_id": "External_5300", "citing_paper_year": 2010, "cited_paper_year": 2009, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "praat doing phonetics by computer retrieved", "cited_author_ids": ["Paul Boersma", "David Weenink"], "citing_author_ids": null, "extended_context": "Phonetic and prosodic segmentation and annotation were performed independently and in parallel by two annotators and then an agreed upon version was produced with the supervision of an expert annotator , for more information see Gr cents nnum ( 2006 ) . The Praat tool was used ( Boersma and Weenink , 2009 ) . The feedback expressions we analyse here are Yes and No expressions , i.e. in Danish words like ja ( yes ) , jo ( yes in a negative context ) , jamen ( yes but , well ) , nej ( no ) , nceh ( no ) .", "section_number": 2, "section_title": null, "intent": "Uses", "cite_marker_offset": [26, 52], "sents_before": [[{"index": 1, "word": "The", "lemma": "the", "after": " ", "pos": "DT", "characterOffsetEnd": 1020, "segment_span": [0, 12], "characterOffsetBegin": 1017, "originalText": "The", "ArgType": null, "before": " "}, {"index": 2, "word": "Praat", "lemma": "Praat", "after": " ", "pos": "NNP", "characterOffsetEnd": 1026, "segment_span": [0, 12], "characterOffsetBegin": 1021, "originalText": "Praat", "ArgType": null, "before": " "}, {"index": 3, "word": "tool", "lemma": "tool", "after": " ", "pos": "NN", "characterOffsetEnd": 1031, "segment_span": [0, 12], "characterOffsetBegin": 1027, "originalText": "tool", "ArgType": null, "before": " "}, {"index": 4, "word": "was", "lemma": "be", 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{"text": "The implementation has been inspired by experience in extracting information from very large corpora ( Curran and Moens , 2002 ) and performing experiments on maximum entropy sequence tagging ( Curran and Clark , 2003 ; Clark et al. , 2003 ) .", "citing_paper_id": "W03-0806", "cited_paper_id": "E03-1071", "citing_paper_year": 2003, "cited_paper_year": 2003, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "investigating gis and smoothing for maximum entropy taggers", "cited_author_ids": ["James R Curran", "Stephen Clark"], "citing_author_ids": null, "extended_context": "We can also load a lexicon into memory that is shared between all of the components , reducing the memory use . The implementation has been inspired by experience in extracting information from very large corpora ( Curran and Moens , 2002 ) and performing experiments on maximum entropy sequence tagging ( Curran and Clark , 2003 ; Clark et al. , 2003 ) . 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{"text": "Our work is inspired by the latent left-linking model in Chang et al. ( 2013 ) and the ILP formulation from Chang et al. ( 2011 ) .", "citing_paper_id": "K15-1002", "cited_paper_id": "D13-1057", "citing_paper_year": 2015, "cited_paper_year": 2013, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "a constrained latent variable model for coreference resolution", "cited_author_ids": ["K-W Chang", "R Samdani", "D Roth"], "citing_author_ids": null, "extended_context": "This section describes our joint coreference resolution and mention head detection framework . Our work is inspired by the latent left-linking model in Chang et al. ( 2013 ) and the ILP formulation from Chang et al. ( 2011 ) . 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( 2011 ) .", "citation_id": "K15-1002_10", "citation_excerpt_index": 0, "section_name": null}
{"text": "Furthermore , the availability of rich ontological resources , in the form of the Unified Medical Language System ( UMLS ) ( Lindberg et al. , 1993 ) , and the availability of software that leverages this knowledge -- MetaMap ( Aronson , 2001 ) for concept identification and SemRep ( Rindflesch and Fiszman , 2003 ) for relation extraction -- provide a foundation for studying the role of semantics in various tasks .", "citing_paper_id": "W06-3309", "cited_paper_id": "External_8545", "citing_paper_year": 2006, "cited_paper_year": 2003, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "the interaction of domain knowledge and linguistic structure in natural language processing interpreting hypernymic propositions in biomedical text", "cited_author_ids": ["Thomas C Rindflesch", "Marcelo Fiszman"], "citing_author_ids": null, "extended_context": "( NLM ) , which also serves as a readily available corpus of abstracts for our experiments . Furthermore , the availability of rich ontological resources , in the form of the Unified Medical Language System ( UMLS ) ( Lindberg et al. , 1993 ) , and the availability of software that leverages this knowledge -- MetaMap ( Aronson , 2001 ) for concept identification and SemRep ( Rindflesch and Fiszman , 2003 ) for relation extraction -- provide a foundation for studying the role of semantics in various tasks . McKnight and Srinivasan ( 2003 ) have previously examined the task of categorizing sentences in medical abstracts using supervised discriminative machine learning techniques .", "section_number": 2, "section_title": null, "intent": "Background", "cite_marker_offset": [285, 314], "sents_before": [[{"index": 1, "word": "Furthermore", "lemma": "furthermore", "after": "", "pos": "RB", "characterOffsetEnd": 100, "segment_span": [0, 73], "characterOffsetBegin": 89, "originalText": "Furthermore", "ArgType": null, "before": " "}, {"index": 2, "word": ",", "lemma": ",", "after": " ", "pos": ",", "characterOffsetEnd": 101, "segment_span": [0, 73], "characterOffsetBegin": 100, "originalText": ",", "ArgType": null, "before": ""}, {"index": 3, "word": "the", "lemma": "the", "after": " ", "pos": "DT", "characterOffsetEnd": 105, "segment_span": [0, 73], "characterOffsetBegin": 102, "originalText": "the", "ArgType": null, "before": " "}, {"index": 4, "word": "availability", "lemma": "availability", 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{"text": "The names given to the components vary ; they have been called `` strategic '' and `` tactical '' components ( e.g. , McKeown 1985 ; Thompson 1977 ; Danlos 1987 ) 1 , `` planning '' and `` realization '' ( e.g. , McDonald 1983 ; Hovy 1988a ) , or simply `` what to say '' versus `` how to say it '' ( e.g. , Danlos 1987 ; Reithinger 1990 ) .", "citing_paper_id": "J00-2001", "cited_paper_id": "External_80545", "citing_paper_year": 2000, "cited_paper_year": 1988, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "generating natural language linder pragmatic constraints lawrence erlbaum", "cited_author_ids": ["Eduard H Hovy"], "citing_author_ids": null, "extended_context": "The text planning component selects and organizes the information to be expressed in some internal representation and then sends it to the linguistic component , which converts the information from the internal form into grammatical sentences of some natural language . The names given to the components vary ; they have been called `` strategic '' and `` tactical '' components ( e.g. , McKeown 1985 ; Thompson 1977 ; Danlos 1987 ) 1 , `` planning '' and `` realization '' ( e.g. , McDonald 1983 ; Hovy 1988a ) , or simply `` what to say '' versus `` how to say it '' ( e.g. , Danlos 1987 ; Reithinger 1990 ) . 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{"text": "Over the last decade there has been a lot of interest in developing tutorial dialogue systems that understand student explanations ( Jordan et al. , 2006 ; Graesser et al. , 1999 ; Aleven et al. , 2001 ; Buckley and Wolska , 2007 ; Nielsen et al. , 2008 ; VanLehn et al. , 2007 ) , because high percentages of selfexplanation and student contentful talk are known to be correlated with better learning in humanhuman tutoring ( Chi et al. , 1994 ; Litman et al. , 2009 ; Purandare and Litman , 2008 ; Steinhauser et al. , 2007 ) .", "citing_paper_id": "P10-4003", "cited_paper_id": "External_53558", "citing_paper_year": 2010, "cited_paper_year": 2007, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "towards modelling and using common ground in tutorial dialogue", "cited_author_ids": ["Mark Buckley", "Magdalena Wolska"], "citing_author_ids": null, "extended_context": "Over the last decade there has been a lot of interest in developing tutorial dialogue systems that understand student explanations ( Jordan et al. , 2006 ; Graesser et al. , 1999 ; Aleven et al. , 2001 ; Buckley and Wolska , 2007 ; Nielsen et al. , 2008 ; VanLehn et al. , 2007 ) , because high percentages of selfexplanation and student contentful talk are known to be correlated with better learning in humanhuman tutoring ( Chi et al. , 1994 ; Litman et al. , 2009 ; Purandare and Litman , 2008 ; Steinhauser et al. , 2007 ) . 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{"text": "We use the TRIPS dialogue parser ( Allen et al. , 2007 ) to parse the utterances .", "citing_paper_id": "P10-4003", "cited_paper_id": "W07-1207", "citing_paper_year": 2010, "cited_paper_year": 2007, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "deep linguistic processing for spoken dialogue systems", "cited_author_ids": ["James Allen", "Myroslava Dzikovska", "Mehdi Manshadi", "Mary Swift"], "citing_author_ids": null, "extended_context": "We use the TRIPS dialogue parser ( Allen et al. , 2007 ) to parse the utterances . 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{"text": "In order to address these limitations in a practical way , we conducted a small user study where we asked four judges ( graduate students from the Faculty of Information Technology at Monash University ) to assess the responses generated by our system ( Marom and Zukerman 2007a ) .", "citing_paper_id": "J09-4010", "cited_paper_id": "External_42504", "citing_paper_year": 2009, "cited_paper_year": 2007, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "evaluation of a largescale email response system", "cited_author_ids": ["Y Marom", "I Zukerman"], "citing_author_ids": null, "extended_context": "Further , user-based evaluations of the output produced by our system require the subjects to read relatively long request -- response e-mails , which quickly becomes tedious . In order to address these limitations in a practical way , we conducted a small user study where we asked four judges ( graduate students from the Faculty of Information Technology at Monash University ) to assess the responses generated by our system ( Marom and Zukerman 2007a ) . 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{"text": "The understanding module utilizes ISSS ( Incremental Significant-utterance Sequence Search ) ( Nakano et al. , 1999b ) , which is an integrated parsing and discourse processing method .", "citing_paper_id": "W00-1017", "cited_paper_id": "P99-1026", "citing_paper_year": 2000, "cited_paper_year": 1999, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "understanding unsegmented user utterances in realtime spoken dialogue systems", "cited_author_ids": ["Mikio Nakano", "Noboru Miyazalci", "Jun-ichi Hirasawa", "Kohji Dohsaka", "Takeshi Kawabata"], "citing_author_ids": null, "extended_context": "The language understanding module receives word hypotheses from the speech recognition module and incrementally understands the sequence of the word hypotheses to update the dialogue state , in which the result of understanding and discourse information are represented by a frame ( i.e. , attribute-value pairs ) . The understanding module utilizes ISSS ( Incremental Significant-utterance Sequence Search ) ( Nakano et al. , 1999b ) , which is an integrated parsing and discourse processing method . ISSS enables the incremental understanding of user utterances that are not segmented into sentences prior to parsing by incrementally finding the most plausible sequence of sentences ( or signcant utterances in the ISSS terms ) out of the possible sentence sequences for the input word sequence .", "section_number": 3, "section_title": null, "intent": "Uses", "cite_marker_offset": [95, 115], "sents_before": [[{"index": 1, "word": "The", "lemma": "the", "after": " ", "pos": "DT", "characterOffsetEnd": 314, "segment_span": [0, 19], "characterOffsetBegin": 311, "originalText": "The", "ArgType": null, "before": " "}, {"index": 2, "word": "understanding", "lemma": "understanding", "after": " ", "pos": "NN", "characterOffsetEnd": 328, "segment_span": [0, 19], "characterOffsetBegin": 315, "originalText": "understanding", "ArgType": null, "before": " "}, {"index": 3, "word": "module", "lemma": "module", "after": " ", "pos": "NN", "characterOffsetEnd": 335, "segment_span": [0, 19], 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{"text": "We applied our system to the XTAG English grammar ( The XTAG Research Group , 2001 ) 3 , which is a large-scale FB-LTAG grammar for English .", "citing_paper_id": "W01-1510", "cited_paper_id": "External_60", "citing_paper_year": 2001, "cited_paper_year": 2001, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "a lexicalized tree adjoining grammar for english", "cited_author_ids": ["The XTAG Research Group"], "citing_author_ids": null, "extended_context": "LiLFeS is one of the fastest inference engines for processing feature structure logic , and efficient HPSG parsers have already been built on this system ( Nishida et al. , 1999 ; Torisawa et al. , 2000 ) . We applied our system to the XTAG English grammar ( The XTAG Research Group , 2001 ) 3 , which is a large-scale FB-LTAG grammar for English . 2The RenTAL system is available at : http://www-tsujii.is.s.u-tokyo.ac.jp/rental/ 3We used the grammar attached to the latest distribution of an LTAG parser which we used for the parsing experiment .", "section_number": 5, "section_title": null, "intent": "Uses", "cite_marker_offset": [70, 82], "sents_before": [[{"index": 1, "word": "We", "lemma": "we", "after": " ", "pos": "PRP", "characterOffsetEnd": 269, "segment_span": [0, 19], "characterOffsetBegin": 267, "originalText": "We", "ArgType": "subj", "before": " "}, {"index": 2, "word": "applied", "characterOffsetEnd": 277, "after": " ", "pos": "VBD", "is_root": true, "lemma": "apply", "segment_span": [0, 19], "tense": "D", "characterOffsetBegin": 270, "originalText": "applied", "ArgType": "verb", "before": " "}, {"index": 3, "word": "our", "lemma": "our", "after": " ", "pos": "PRP$", 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{"text": "In this paper , we extend two classes of model adaptation methods ( i.e. , model interpolation and error-driven learning ) , which have been well studied in statistical language modeling for speech and natural language applications ( e.g. , Bacchiani et al. , 2004 ; Bellegarda , 2004 ; Gao et al. , 2006 ) , to ranking models for Web search applications .", "citing_paper_id": "D09-1053", "cited_paper_id": "N04-4006", "citing_paper_year": 2009, "cited_paper_year": 2004, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "language model adaptation with map estimation and the perceptron algorithm", "cited_author_ids": ["M Bacchiani", "B Roark", "M Saraclar"], "citing_author_ids": null, "extended_context": "In this paper , we extend two classes of model adaptation methods ( i.e. , model interpolation and error-driven learning ) , which have been well studied in statistical language modeling for speech and natural language applications ( e.g. , Bacchiani et al. , 2004 ; Bellegarda , 2004 ; Gao et al. , 2006 ) , to ranking models for Web search applications . We have evaluated our methods on two adaptation experiments over a wide variety of datasets where the in-domain datasets bear different levels of similarities to their background datasets .", "section_number": 6, "section_title": null, "intent": "Background", "cite_marker_offset": [241, 264], "sents_before": [[{"index": 1, "word": "In", "lemma": "in", "after": " ", "pos": "IN", "characterOffsetEnd": 2, "segment_span": [0, 64], "characterOffsetBegin": 0, "originalText": "In", "ArgType": null, "before": ""}, {"index": 2, "word": "this", "lemma": "this", "after": " ", "pos": "DT", "characterOffsetEnd": 7, "segment_span": [0, 64], "characterOffsetBegin": 3, "originalText": "this", "ArgType": null, "before": " "}, {"index": 3, "word": "paper", "lemma": "paper", "after": "", "pos": "NN", "characterOffsetEnd": 13, "segment_span": [0, 64], "characterOffsetBegin": 8, "originalText": "paper", "ArgType": null, "before": " "}, {"index": 4, "word": ",", "lemma": ",", "after": " ", "pos": ",", 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{"text": "Since sentences can refer to events described by other sentences , we may need also a quotation operator ; Perlis ( 1985 ) describes how first order logic can be augmented with such an operator .", "citing_paper_id": "J91-2003", "cited_paper_id": "External_76216", "citing_paper_year": 1991, "cited_paper_year": 1985, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "languages with self reference i foundationsquot", "cited_author_ids": ["D Perlis"], "citing_author_ids": null, "extended_context": "The reader may consult recent papers on this subject ( e.g. Moens and Steedman 1987 ; Webber 1987 ) to see what a formal interpretation of events in time might look like . Since sentences can refer to events described by other sentences , we may need also a quotation operator ; Perlis ( 1985 ) describes how first order logic can be augmented with such an operator . Extending and revising Jackendoff 's ( 1983 ) formalism seems to us a correct method to achieve the correspondence between syntax and semantics expressed in the grammatical constraint ( `` that one should prefer a semantic theory that explains otherwise arbitrary generalizations about the syntax and the lexicon '' -- ibid . )", "section_number": 1, "section_title": null, "intent": "Background", "cite_marker_offset": [107, 122], "sents_before": [[{"index": 1, "word": "Since", "lemma": "since", "after": " ", "pos": "IN", "characterOffsetEnd": 700, "segment_span": [0, 10], "characterOffsetBegin": 695, "originalText": "Since", "ArgType": null, "before": " "}, {"index": 2, "word": "sentences", "lemma": "sentence", "after": " ", "pos": "NNS", "characterOffsetEnd": 710, "segment_span": [0, 10], "characterOffsetBegin": 701, "originalText": "sentences", "ArgType": "subj", "before": " "}, {"index": 3, "word": "can", "lemma": "can", "after": " ", "pos": "MD", "characterOffsetEnd": 714, 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{"text": "A possible future direction would be to compare the query string to retrieved results using a method similar to that of Tsuruoka and Tsujii ( 2003 ) .", "citing_paper_id": "W11-0218", "cited_paper_id": "W03-1306", "citing_paper_year": 2011, "cited_paper_year": 2003, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "boosting precision and recall of dictionarybased protein name recognition", "cited_author_ids": ["Y Tsuruoka", "J Tsujii"], "citing_author_ids": null, "extended_context": "It may be that our notion of distance to lexical resource entries is too naive . A possible future direction would be to compare the query string to retrieved results using a method similar to that of Tsuruoka and Tsujii ( 2003 ) . This would enable us to retain the advantage of fast approximate string matching , thus being able to utilise larger lexical resources than if we were to calculate sophisticated alignments for each lexical entry .", "section_number": 6, "section_title": null, "intent": "Future", "cite_marker_offset": [120, 148], "sents_before": [[{"index": 1, "word": "A", "lemma": "a", "after": " ", "pos": "DT", "characterOffsetEnd": 230, "segment_span": [0, 14], "characterOffsetBegin": 229, "originalText": "A", "ArgType": null, "before": " "}, {"index": 2, "word": "possible", "lemma": "possible", "after": " ", "pos": "JJ", "characterOffsetEnd": 239, "segment_span": [0, 14], "characterOffsetBegin": 231, "originalText": "possible", "ArgType": null, "before": " "}, {"index": 3, "word": "future", "lemma": "future", "after": " ", "pos": "JJ", "characterOffsetEnd": 246, "segment_span": [0, 14], "characterOffsetBegin": 240, "originalText": "future", "ArgType": null, "before": " "}, {"index": 4, "word": 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{"text": "description-level lexical rules ( DLRs ; Meurers 1995 ) .5 2.2.1 Meta-Level Lexical Rules .", "citing_paper_id": "J97-4003", "cited_paper_id": "External_41778", "citing_paper_year": 1997, "cited_paper_year": 1995, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "towards a semantics for lexical rules as used in hpsg", "cited_author_ids": ["Detmar Meurers"], "citing_author_ids": null, "extended_context": "Two formalizations of lexical rules as used by HPSG linguists have been proposed , the meta-level lexical rules ( MLRs ; Calcagno 1995 ; Calcagno and Pollard 1995 ) and the . description-level lexical rules ( DLRs ; Meurers 1995 ) .5 2.2.1 Meta-Level Lexical Rules . 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{"text": "All EBMT systems , from the initial proposal by Nagao ( 1984 ) to the recent collection of Carl and Way ( 2003 ) , are premised on the availability of subsentential alignments derived from the input bitext .", "citing_paper_id": "J03-3004", "cited_paper_id": "External_3000", "citing_paper_year": 2003, "cited_paper_year": 1984, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "a framework of a mechanical translation between japanese and english by analogy principle", "cited_author_ids": ["Makoto Nagao"], "citing_author_ids": null, "extended_context": "Deriving Translation Resources from Web-Based MT Systems All EBMT systems , from the initial proposal by Nagao ( 1984 ) to the recent collection of Carl and Way ( 2003 ) , are premised on the availability of subsentential alignments derived from the input bitext . There is a wealth of literature on trying to establish subsentential translations from a bilingual corpus .3 Kay and R ¨ oscheisen ( 1993 ) attempt to extract a bilingual dictionary using a hybrid method of sentence and word alignment on the assumption that the ( source , target ) words have a similar distribution .", "section_number": 1, "section_title": null, "intent": "Background", "cite_marker_offset": [48, 62], "sents_before": [[{"index": 1, "word": "All", "lemma": "all", "after": " ", "pos": "DT", "characterOffsetEnd": 3, "segment_span": [0, 38], "characterOffsetBegin": 0, "originalText": "All", "ArgType": null, "before": ""}, {"index": 2, "word": "EBMT", "lemma": "ebmt", "after": " ", "pos": "NN", "characterOffsetEnd": 8, "segment_span": [0, 38], "characterOffsetBegin": 4, "originalText": "EBMT", "ArgType": null, "before": " "}, {"index": 3, "word": "systems", "lemma": "system", "after": "", "pos": "NNS", "characterOffsetEnd": 16, "segment_span": [0, 38], "characterOffsetBegin": 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{"text": "The necessity of this kind of merging of arguments has been recognized before : Charniak and McDermott ( 1985 ) call it abductive unification/matching , Hobbs ( 1978 , 1979 ) refers to such operations using the terms knitting or petty conversational implicature .", "citing_paper_id": "J91-2003", "cited_paper_id": "External_1853", "citing_paper_year": 1991, "cited_paper_year": 1978, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "resolving pronoun referencesquot", "cited_author_ids": ["J R Hobbs"], "citing_author_ids": null, "extended_context": "This equality i = i ' can not be proven , but it may be reasonably assumed -- we know that in this case the infection i ' caused the illness , which , in turn , caused the death . The necessity of this kind of merging of arguments has been recognized before : Charniak and McDermott ( 1985 ) call it abductive unification/matching , Hobbs ( 1978 , 1979 ) refers to such operations using the terms knitting or petty conversational implicature . Neither Hobbs nor Charniak and McDermott tried then to make this notion precise , but the paper by Hobbs et al. 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{"text": "In a number of proposals , lexical generalizations are captured using lexical underspecification ( Kathol 1994 ; Krieger and Nerbonne 1992 ;", "citing_paper_id": "J97-4003", "cited_paper_id": "External_18901", "citing_paper_year": 1997, "cited_paper_year": 1992, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "featurebased inheritance networks for computational lexicons", "cited_author_ids": ["Hans-Ulrich Krieger", "John Nerbonne"], "citing_author_ids": null, "extended_context": "Lexical rules have not gone unchallenged as a mechanism for expressing generalizations over lexical information . In a number of proposals , lexical generalizations are captured using lexical underspecification ( Kathol 1994 ; Krieger and Nerbonne 1992 ; Riehemann 1993 ; Oliva 1994 ; Frank 1994 ; Opalka 1995 ; Sanfilippo 1995 ) .", "section_number": 4, "section_title": null, "intent": "CompareOrContrast", "cite_marker_offset": [113, 138], "sents_before": [[{"index": 1, "word": "In", "lemma": "in", "after": " ", "pos": "IN", "characterOffsetEnd": 115, "segment_span": [0, 21], "characterOffsetBegin": 113, "originalText": "In", "ArgType": null, "before": " "}, {"index": 2, "word": "a", "lemma": "a", "after": " ", "pos": "DT", "characterOffsetEnd": 117, "segment_span": [0, 21], "characterOffsetBegin": 116, "originalText": "a", "ArgType": null, "before": " "}, {"index": 3, "word": "number", "lemma": "number", "after": " ", "pos": "NN", "characterOffsetEnd": 124, "segment_span": [0, 21], "characterOffsetBegin": 118, "originalText": "number", "ArgType": null, "before": " "}, {"index": 4, "word": "of", 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{"text": "These keywords are potentially useful features because some of them are subclasses of the ACE SCs shown in the left column of Table 1 , while others appear to be correlated with these ACE SCs .2 ( 6 ) INDUCED CLASS : Since the first-sense heuristic used in the previous feature may not be accurate in capturing the SC of an NP , we employ a corpusbased method for inducing SCs that is motivated by research in lexical semantics ( e.g. , Hearst ( 1992 ) ) .", "citing_paper_id": "P07-1068", "cited_paper_id": "External_2967", "citing_paper_year": 2007, "cited_paper_year": 1992, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "automatic acquisition of hyponyms from large text corpora", "cited_author_ids": ["M Hearst"], "citing_author_ids": null, "extended_context": "( 5 ) WN CLASS : For each keyword w shown in the right column of Table 1 , we determine whether the head noun of NPZ is a hyponym of w in WordNet , using only the first WordNet sense of NPZ .1 If so , we create a WN CLASS feature with w as its value . These keywords are potentially useful features because some of them are subclasses of the ACE SCs shown in the left column of Table 1 , while others appear to be correlated with these ACE SCs .2 ( 6 ) INDUCED CLASS : Since the first-sense heuristic used in the previous feature may not be accurate in capturing the SC of an NP , we employ a corpusbased method for inducing SCs that is motivated by research in lexical semantics ( e.g. , Hearst ( 1992 ) ) . Given a large , unannotated corpus3 , we use IdentiFinder to label each NE with its NE type and MINIPAR to extract all the appositive relations .", "section_number": 2, "section_title": null, "intent": "Motivation", "cite_marker_offset": [437, 452], "sents_before": [[{"index": 1, "word": "These", "lemma": "these", "after": " ", "pos": "DT", "characterOffsetEnd": 249, "segment_span": [0, 71], "characterOffsetBegin": 244, "originalText": "These", "ArgType": null, "before": " "}, {"index": 2, "word": "keywords", "lemma": "keyword", "after": " ", "pos": "NNS", "characterOffsetEnd": 258, "segment_span": [0, 71], "characterOffsetBegin": 250, "originalText": "keywords", "ArgType": "subj", "before": " "}, {"index": 3, "word": "are", "lemma": "be", "after": " ", "pos": "VBP", "characterOffsetEnd": 262, "segment_span": [0, 71], "characterOffsetBegin": 259, "originalText": "are", "ArgType": null, "before": " "}, {"index": 4, "word": "potentially", "lemma": "potentially", "after": " ", "pos": 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"citation_id": "P07-1068_5", "citation_excerpt_index": 0, "section_name": "introduction"}
{"text": "Other psycholing-uistic studies that confirm the validity of paragraph units can be found in Black and Bower ( 1979 ) and Haberlandt et al. ( 1980 ) .", "citing_paper_id": "J91-2003", "cited_paper_id": "External_34288", "citing_paper_year": 1991, "cited_paper_year": 1979, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "episodes as chunks in narrative memoryquot", "cited_author_ids": ["J B Black", "G H Bower"], "citing_author_ids": null, "extended_context": "Bond and Hayes found three major formal devices that are used , by readers , to identify a paragraph : ( 1 ) the repetition of content words ( nouns , verbs , adjectives , adverbs ) ; ( 2 ) pronoun reference ; and ( 3 ) paragraph length , as determined by spatial and/or sentence-count information . Other psycholing-uistic studies that confirm the validity of paragraph units can be found in Black and Bower ( 1979 ) and Haberlandt et al. ( 1980 ) . The textualist approach to paragraph analysis is exemplified by E. J. 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{"text": "The bottom panel of table 1 lists the results for the chosen lexicalized model ( SSN-Freq > 200 ) and five recent statistical parsers ( Ratnaparkhi , 1999 ; Collins , 1999 ; Charniak , 2000 ; Collins , 2000 ; Bod , 2001 ) .", "citing_paper_id": "E03-1002", "cited_paper_id": "P01-1010", "citing_paper_year": 2003, "cited_paper_year": 2001, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "what is the minimal set of fragments that achieves maximal parse accuracy", "cited_author_ids": ["Rens Bod"], "citing_author_ids": null, "extended_context": "The Tags model also does much better than the only other broad coverage neural network parser ( Costa et al. , 2001 ) . The bottom panel of table 1 lists the results for the chosen lexicalized model ( SSN-Freq > 200 ) and five recent statistical parsers ( Ratnaparkhi , 1999 ; Collins , 1999 ; Charniak , 2000 ; Collins , 2000 ; Bod , 2001 ) . 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Nevertheless , the full document text is present in most systems , sometimes as the only feature ( Sugiyama and Okumura , 2007 ) and sometimes in combination with others see for instance ( Chen and Martin , 2007 ; Popescu and Magnini , 2007 ) - . 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{"text": "As a result , researchers have re-adopted the once-popular knowledge-rich approach , investigating a variety of semantic knowledge sources for common noun resolution , such as the semantic relations between two NPs ( e.g. , Ji et al. ( 2005 ) ) , their semantic similarity as computed using WordNet ( e.g. , Poesio et al. ( 2004 ) ) or Wikipedia ( Ponzetto and Strube , 2006 ) , and the contextual role played by an NP ( see Bean and Riloff ( 2004 ) ) .", "citing_paper_id": "P07-1068", "cited_paper_id": "H05-1003", "citing_paper_year": 2007, "cited_paper_year": 2005, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "using semantic relations to refine coreference decisions", "cited_author_ids": ["H Ji", "D Westbrook", "R Grishman"], "citing_author_ids": null, "extended_context": "In fact , semantics plays a crucially important role in the resolution of common NPs , allowing us to identify the coreference relation between two lexically dissimilar common nouns ( e.g. , talks and negotiations ) and to eliminate George W. Bush from the list of candidate antecedents of the city , for instance . As a result , researchers have re-adopted the once-popular knowledge-rich approach , investigating a variety of semantic knowledge sources for common noun resolution , such as the semantic relations between two NPs ( e.g. , Ji et al. ( 2005 ) ) , their semantic similarity as computed using WordNet ( e.g. , Poesio et al. ( 2004 ) ) or Wikipedia ( Ponzetto and Strube , 2006 ) , and the contextual role played by an NP ( see Bean and Riloff ( 2004 ) ) . Another type of semantic knowledge that has been employed by coreference resolvers is the semantic class ( SC ) of an NP , which can be used to disallow coreference between semantically incompatible NPs .", "section_number": 2, "section_title": null, "intent": "Background", "cite_marker_offset": [224, 242], "sents_before": [[{"index": 1, "word": "As", "lemma": "as", "after": " ", "pos": "IN", "characterOffsetEnd": 932, "segment_span": [0, 12], "characterOffsetBegin": 930, "originalText": "As", "ArgType": null, "before": " "}, {"index": 2, "word": "a", "lemma": "a", "after": " ", "pos": "DT", "characterOffsetEnd": 934, "segment_span": [0, 12], "characterOffsetBegin": 933, "originalText": "a", "ArgType": null, "before": " "}, {"index": 3, "word": "result", "lemma": "result", "after": "", "pos": "NN", "characterOffsetEnd": 941, "segment_span": [0, 12], "characterOffsetBegin": 935, "originalText": "result", "ArgType": null, "before": " "}, {"index": 4, "word": ",", "lemma": ",", "after": " 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{"text": "We built a two-stage baseline system , using the perceptron segmentation model from our previous work ( Zhang and Clark , 2007 ) and the perceptron POS tagging model from Collins ( 2002 ) .", "citing_paper_id": "P08-1101", "cited_paper_id": "P07-1106", "citing_paper_year": 2008, "cited_paper_year": 2007, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "chinese segmentation with a wordbased perceptron algorithm", "cited_author_ids": ["Yue Zhang", "Stephen Clark"], "citing_author_ids": null, "extended_context": "We built a two-stage baseline system , using the perceptron segmentation model from our previous work ( Zhang and Clark , 2007 ) and the perceptron POS tagging model from Collins ( 2002 ) . We use baseline system to refer to the system which performs segmentation first , followed by POS tagging ( using the single-best segmentation ) ; baseline segmentor to refer to the segmentor from ( Zhang and Clark , 2007 ) which performs segmentation only ; and baseline POStagger to refer to the Collins tagger which performs POS tagging only ( given segmentation ) .", "section_number": 3, "section_title": null, "intent": "Extends", "cite_marker_offset": [104, 126], "sents_before": [[{"index": 1, "word": "We", "lemma": "we", "after": " ", "pos": "PRP", "characterOffsetEnd": 2, "segment_span": [0, 7], "characterOffsetBegin": 0, "originalText": "We", "ArgType": "subj", "before": ""}, {"index": 2, "word": "built", "characterOffsetEnd": 8, "after": " ", "pos": "VBD", "is_root": true, "lemma": "build", "segment_span": [0, 7], "tense": "D", "characterOffsetBegin": 3, "originalText": "built", "ArgType": "verb", "before": " "}, {"index": 3, "word": "a", "lemma": "a", "after": " ", "pos": "DT", 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{"text": "Note that although our current system uses MeSH headings assigned by human indexers , manually assigned terms can be replaced with automatic processing if needed ( Aronson et al. 2004 ) .", "citing_paper_id": "J07-1005", "cited_paper_id": "External_57139", "citing_paper_year": 2007, "cited_paper_year": 2004, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "the nlm indexing initiative’s medical text indexer", "cited_author_ids": ["Alan R Aronson", "James G Mork", "Clifford W Gay", "Susanne M Humphrey", "Willie J Rogers"], "citing_author_ids": null, "extended_context": "The function α ( t ) maps a MeSH term to a positive score if the term is a positive indicator for that particular task type , or a negative score if the term is a negative indicator for the clinical task . Note that although our current system uses MeSH headings assigned by human indexers , manually assigned terms can be replaced with automatic processing if needed ( Aronson et al. 2004 ) . 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{"text": "Furthermore , medical terminology is characterized by a typical mix of Latin and Greek roots with the corresponding host language ( e.g. , German ) , often referred to as neo-classical compounding ( McCray et al. , 1988 ) .", "citing_paper_id": "W02-0309", "cited_paper_id": "External_80942", "citing_paper_year": 2002, "cited_paper_year": 1988, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "the semantic structure of neoclassical compounds", "cited_author_ids": ["A McCray", "A Browne", "D Moore"], "citing_author_ids": null, "extended_context": "Hence , enumerating morphological variants in a semi-automatically generated lexicon , such as proposed for French ( Zweigenbaum et al. , 2001 ) , turns out to be infeasible , at least for German and related languages . Furthermore , medical terminology is characterized by a typical mix of Latin and Greek roots with the corresponding host language ( e.g. , German ) , often referred to as neo-classical compounding ( McCray et al. , 1988 ) . While this is simply irrelevant for general-purpose morphological analyzers , dealing with such phenomena is crucial for any attempt to cope adequately with medical free-texts in an IR setting ( Wolff , 1984 ) .", "section_number": 2, "section_title": null, "intent": "Background", "cite_marker_offset": [199, 219], "sents_before": [[{"index": 1, "word": "Furthermore", "lemma": "furthermore", "after": "", "pos": "RB", "characterOffsetEnd": 11, "segment_span": [0, 39], "characterOffsetBegin": 0, "originalText": "Furthermore", "ArgType": null, "before": ""}, {"index": 2, "word": ",", "lemma": ",", "after": " ", "pos": ",", "characterOffsetEnd": 12, "segment_span": [0, 39], "characterOffsetBegin": 11, "originalText": ",", "ArgType": null, "before": ""}, {"index": 3, "word": "medical", "lemma": "medical", "after": " ", "pos": "JJ", "characterOffsetEnd": 20, "segment_span": [0, 39], "characterOffsetBegin": 13, "originalText": "medical", "ArgType": null, "before": " "}, {"index": 4, "word": 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{"text": "To model d ( FWi − 1 , S → T ) , d ( FWi +1 , S → T ) , i.e. whether Li , S → T and Ri , S → T extend beyond the neighboring function word phrase pairs , we utilize the pairwise dominance model of Setiawan et al. ( 2009 ) .", "citing_paper_id": "D10-1052", "cited_paper_id": "P09-1037", "citing_paper_year": 2010, "cited_paper_year": 2009, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "topological ordering of function words in hierarchical phrasebased translation", "cited_author_ids": ["Hendra Setiawan", "Min Yen Kan", "Haizhou Li", "Philip Resnik"], "citing_author_ids": null, "extended_context": "jections of the function word and the neighboring phrase are adjacent or separated by an intervening phrase . To model d ( FWi − 1 , S → T ) , d ( FWi +1 , S → T ) , i.e. whether Li , S → T and Ri , S → T extend beyond the neighboring function word phrase pairs , we utilize the pairwise dominance model of Setiawan et al. ( 2009 ) . Taking d ( FWi − 1 , S → T ) as a case in point , this model takes the form Pdom ( d ( FWi − 1 , S → T ) | Yi − 1 , S → T , Yi , S → T ) , where d takes one of the following four dominance values : leftFirst , rightFirst , dontCare , or neither .", "section_number": 4, "section_title": null, "intent": "Uses", "cite_marker_offset": [207, 231], "sents_before": [[{"index": 1, "word": "To", "lemma": "to", "after": " ", "pos": "TO", "characterOffsetEnd": 111, "segment_span": [0, 45], "characterOffsetBegin": 109, "originalText": "To", "ArgType": null, "before": " "}, {"index": 2, "word": "model", "characterOffsetEnd": 117, "after": " ", "pos": "VB", "is_root": true, "lemma": "model", "segment_span": [0, 45], "tense": "B", "characterOffsetBegin": 112, "originalText": "model", "ArgType": null, "before": " "}, {"index": 3, "word": "d", "lemma": "d", "after": "", "pos": "NN", "characterOffsetEnd": 119, "segment_span": [0, 45], "characterOffsetBegin": 118, "originalText": "d", "ArgType": "dobj", 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{"text": "For instance , Sells ( 1985 , p. 8 ) says that the sentence `` Reagan thinks bananas , '' which is otherwise strange , is in fact acceptable if it occurs as an answer to the question `` What is Kissinger 's favorite fruit ? ''", "citing_paper_id": "J91-2003", "cited_paper_id": "External_15145", "citing_paper_year": 1991, "cited_paper_year": 1985, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "lectures on contemporary syntactic theories csli lecture notes", "cited_author_ids": ["P Sells"], "citing_author_ids": null, "extended_context": "A paragraph can be thought of as a grammatical unit in the following sense : it is the discourse unit in which a functional ( or a predicate-argument ) structure can be definitely assigned to sentences/strings . For instance , Sells ( 1985 , p. 8 ) says that the sentence `` Reagan thinks bananas , '' which is otherwise strange , is in fact acceptable if it occurs as an answer to the question `` What is Kissinger 's favorite fruit ? 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{"text": "The most detailed evaluation of link tokens to date was performed by ( Macklovitch & Hannan , 1996 ) , who trained Brown et al. 's Model 2 on 74 million words of the Canadian Hansards .", "citing_paper_id": "P97-1063", "cited_paper_id": "External_19463", "citing_paper_year": 1997, "cited_paper_year": 1996, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "line em up advances in alignment technology and their impact on translation support toolsquot", "cited_author_ids": ["E Macklovitch", "M-L Hannan"], "citing_author_ids": null, "extended_context": "The most detailed evaluation of link tokens to date was performed by ( Macklovitch & Hannan , 1996 ) , who trained Brown et al. 's Model 2 on 74 million words of the Canadian Hansards . 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{"text": "While we have observed reasonable results with both G2 and Fisher 's exact test , we have not yet discussed how these results compare to the results that can be obtained with a technique commonly used in corpus linguistics based on the mutual information ( MI ) measure ( Church and Hanks 1990 ) :", "citing_paper_id": "J00-3001", "cited_paper_id": "External_244", "citing_paper_year": 2000, "cited_paper_year": 1990, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "word association norms mutual information and lexicography", "cited_author_ids": ["Kenneth W Church", "Patrick Hanks"], "citing_author_ids": null, "extended_context": "For the higherfrequency words , Fisher 's exact test leads to a slightly better recall with the same precision scores ( 0.31 for both tests ) . While we have observed reasonable results with both G2 and Fisher 's exact test , we have not yet discussed how these results compare to the results that can be obtained with a technique commonly used in corpus linguistics based on the mutual information ( MI ) measure ( Church and Hanks 1990 ) : In ( 4 ) , y is the seed term and x a potential target word .", "section_number": 2, "section_title": null, "intent": "Background", "cite_marker_offset": [272, 293], "sents_before": [[{"index": 1, "word": "While", "lemma": "while", "after": " ", "pos": "IN", "characterOffsetEnd": 1598, "segment_span": [0, 14], "characterOffsetBegin": 1593, "originalText": "While", "ArgType": null, "before": " "}, {"index": 2, "word": "we", "lemma": "we", "after": " ", "pos": "PRP", "characterOffsetEnd": 1601, "segment_span": [0, 14], "characterOffsetBegin": 1599, "originalText": "we", "ArgType": "subj", "before": " "}, {"index": 3, "word": "have", "lemma": "have", "after": " ", "pos": "VBP", 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compare to the results that can be obtained with a technique commonly used in corpus linguistics based on the mutual information ( MI ) measure ( @@CITATION ) :", "citation_id": "J00-3001_2", "citation_excerpt_index": 0, "section_name": "conclusion"}
{"text": "Morphological alterations of a search term have a negative impact on the recall performance of an information retrieval ( IR ) system ( Choueka , 1990 ; J ¨ appinen and Niemist ¨ o , 1988 ; Kraaij and Pohlmann , 1996 ) , since they preclude a direct match between the search term proper and its morphological variants in the documents to be retrieved .", "citing_paper_id": "W02-0309", "cited_paper_id": "External_45869", "citing_paper_year": 2002, "cited_paper_year": 1990, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "responsa an operational fulltext retrieval system with linguistic components for large corpora", "cited_author_ids": ["Y Choueka"], "citing_author_ids": null, "extended_context": "Morphological alterations of a search term have a negative impact on the recall performance of an information retrieval ( IR ) system ( Choueka , 1990 ; J ¨ appinen and Niemist ¨ o , 1988 ; Kraaij and Pohlmann , 1996 ) , since they preclude a direct match between the search term proper and its morphological variants in the documents to be retrieved . In order to cope with such variation , morphological analysis is concerned with the reverse processing of inflection ( e.g. , ` search ed ' , ` search ing ' ) 1 , derivation ( e.g. , ` search er ' or ` search able ' ) and composition ( e.g. , German ` Blut hoch druck ' [ ` high blood pressure ' ] ) .", "section_number": 2, "section_title": null, "intent": "Background", "cite_marker_offset": [136, 150], "sents_before": [[{"index": 1, "word": "Morphological", "lemma": "morphological", "after": " ", "pos": "JJ", "characterOffsetEnd": 13, "segment_span": [0, 44], "characterOffsetBegin": 0, "originalText": "Morphological", "ArgType": null, "before": ""}, {"index": 2, "word": "alterations", "lemma": "alteration", "after": " ", "pos": "NNS", "characterOffsetEnd": 25, "segment_span": [0, 44], "characterOffsetBegin": 14, "originalText": "alterations", "ArgType": "subj", "before": " "}, {"index": 3, "word": "of", "lemma": "of", "after": " ", "pos": "IN", "characterOffsetEnd": 28, "segment_span": 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{"text": "For shuffling paraphrases , french alternations are partially described in ( Saint-Dizier , 1999 ) and a resource is available which describes alternation and the mapping verbs/alternations for roughly 1 700 verbs .", "citing_paper_id": "W04-0910", "cited_paper_id": "External_40272", "citing_paper_year": 2004, "cited_paper_year": 1999, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "alternations and verb semantic classes for french analysis and class formation chapter 5", "cited_author_ids": ["P Saint-Dizier"], "citing_author_ids": null, "extended_context": "However as for other types of synonymy , distributional analysis and clustering techniques can be used to develop such resources . For shuffling paraphrases , french alternations are partially described in ( Saint-Dizier , 1999 ) and a resource is available which describes alternation and the mapping verbs/alternations for roughly 1 700 verbs . 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{"text": "A more recent approach , advocated by Rappaport Hovav and Levin ( 1998 ) , describes a basic set of event templates corresponding to Vendler 's event classes ( Vendler , 1957 ) : ( 3 ) a. [ x ACT <MANNER> ] ( activity ) b. [ x <STATE> ] ( state ) c. [ BECOME [ x <STATE> ] ] ( achievement ) d. [ x CAUSE [ BECOME [ x <STATE> ] ] ] ( accomplishment )", "citing_paper_id": "N04-2004", "cited_paper_id": "External_4340", "citing_paper_year": 2004, "cited_paper_year": 1957, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "verbs and times", "cited_author_ids": ["Zeno Vendler"], "citing_author_ids": null, "extended_context": "[ [ DO ( he , sweeps ( the floor ) ) ] CAUSE [ BECOME [ clean ( the floor ) ] ] ] Dowty breaks the event described by ( 2 ) into two subevents , the activity of sweeping the floor and its result , the state of the floor being clean . A more recent approach , advocated by Rappaport Hovav and Levin ( 1998 ) , describes a basic set of event templates corresponding to Vendler 's event classes ( Vendler , 1957 ) : ( 3 ) a. [ x ACT <MANNER> ] ( activity ) b. [ x <STATE> ] ( state ) c. [ BECOME [ x <STATE> ] ] ( achievement ) d. [ x CAUSE [ BECOME [ x <STATE> ] ] ] ( accomplishment ) A process called Template Augmentation allows basic event templates to be freely `` augmented '' to any other event template .", "section_number": 3, "section_title": null, "intent": "Background", "cite_marker_offset": [160, 174], "sents_before": [[{"index": 1, "word": "A", "lemma": "a", "after": " ", "pos": "DT", "characterOffsetEnd": 251, "segment_span": [0, 79], "characterOffsetBegin": 250, "originalText": "A", "ArgType": null, "before": " "}, {"index": 2, "word": "more", "lemma": "more", "after": " ", "pos": "RBR", "characterOffsetEnd": 256, "segment_span": [0, 79], "characterOffsetBegin": 252, "originalText": "more", "ArgType": null, "before": " "}, {"index": 3, "word": "recent", "lemma": "recent", "after": " ", "pos": "JJ", "characterOffsetEnd": 263, "segment_span": [0, 79], "characterOffsetBegin": 257, "originalText": "recent", "ArgType": null, "before": " "}, {"index": 4, "word": "approach", "lemma": "approach", "after": 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{"text": "Watanabe ( 1993 ) combines lexical and dependency mappings to form his generalizations .", "citing_paper_id": "J03-3004", "cited_paper_id": "External_30768", "citing_paper_year": 2003, "cited_paper_year": 1993, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "a method for extracting translation patterns from translation examples", "cited_author_ids": ["Hideo Watanabe"], "citing_author_ids": null, "extended_context": "Kaji , Kida , and Morimoto ( 1992 ) identify translationally equivalent phrasal segments and replace such equivalents with variables to generate a set of translation patterns . Watanabe ( 1993 ) combines lexical and dependency mappings to form his generalizations . Other similar approaches include those of Cicekli and G ¨ uvenir ( 1996 ) , McTait and Trujillo ( 1999 ) , Carl ( 1999 ) , and Brown ( 2000 ) , inter alia .", "section_number": 1, "section_title": null, "intent": "Background", "cite_marker_offset": [0, 17], "sents_before": [[{"index": 1, "word": "Watanabe", "lemma": "Watanabe", "after": " ", "pos": "NNP", "characterOffsetEnd": 257, "segment_span": [0, 13], "characterOffsetBegin": 249, "originalText": "Watanabe", "ArgType": "subj", "before": " "}, {"index": 2, "word": "(", "lemma": "-lrb-", "after": "", "pos": "-LRB-", "characterOffsetEnd": 259, "segment_span": [0, 13], "characterOffsetBegin": 258, "originalText": "(", "ArgType": null, "before": " "}, {"index": 3, "word": "1993", "lemma": "1993", "after": "", "pos": "CD", "characterOffsetEnd": 263, "segment_span": [0, 13], "characterOffsetBegin": 259, "originalText": "1993", "ArgType": null, "before": ""}, {"index": 4, "word": ")", "lemma": "-rrb-", "after": " ", "pos": "-RRB-", 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{"text": "Thus for instance , ( Copestake and Flickinger , 2000 ; Copestake et al. , 2001 ) describes a Head Driven Phrase Structure Grammar ( HPSG ) which supports the parallel construction of a phrase structure ( or derived ) tree and of a semantic representation and ( Dalrymple , 1999 ) show how to equip Lexical Functional grammar ( LFG ) with a glue semantics .", "citing_paper_id": "W04-0910", "cited_paper_id": "P01-1019", "citing_paper_year": 2004, "cited_paper_year": 2001, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "an algebra for semantic construction in constraintbased grammars", "cited_author_ids": ["A Copestake", "A Lascarides", "D Flickinger"], "citing_author_ids": null, "extended_context": "`` Semantic grammars '' already exist which describe not only the syntax but also the semantics of natural language . Thus for instance , ( Copestake and Flickinger , 2000 ; Copestake et al. , 2001 ) describes a Head Driven Phrase Structure Grammar ( HPSG ) which supports the parallel construction of a phrase structure ( or derived ) tree and of a semantic representation and ( Dalrymple , 1999 ) show how to equip Lexical Functional grammar ( LFG ) with a glue semantics . These grammars are both efficient and large scale in that they cover an important fragment of the natural language they describe and can be processed by parsers and generators in almost real time .", "section_number": 4, "section_title": null, "intent": "Background", "cite_marker_offset": [56, 79], "sents_before": [[{"index": 1, "word": "Thus", "lemma": "thus", "after": " ", "pos": "RB", "characterOffsetEnd": 117, "segment_span": [0, 18], "characterOffsetBegin": 113, "originalText": "Thus", "ArgType": null, "before": " "}, {"index": 2, "word": "for", "lemma": "for", "after": " ", "pos": "IN", "characterOffsetEnd": 121, "segment_span": [0, 18], "characterOffsetBegin": 118, "originalText": "for", "ArgType": null, "before": " "}, {"index": 3, "word": "instance", "lemma": "instance", "after": "", "pos": "NN", "characterOffsetEnd": 130, "segment_span": [0, 18], "characterOffsetBegin": 122, "originalText": "instance", "ArgType": null, "before": " "}, {"index": 4, "word": ",", "lemma": ",", 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{"text": "The reordering models we describe follow our previous work using function word models for translation ( Setiawan et al. , 2007 ; Setiawan et al. , 2009 ) .", "citing_paper_id": "D10-1052", "cited_paper_id": "P09-1037", "citing_paper_year": 2010, "cited_paper_year": 2009, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "topological ordering of function words in hierarchical phrasebased translation", "cited_author_ids": ["Hendra Setiawan", "Min Yen Kan", "Haizhou Li", "Philip Resnik"], "citing_author_ids": null, "extended_context": "The reordering models we describe follow our previous work using function word models for translation ( Setiawan et al. , 2007 ; Setiawan et al. , 2009 ) . 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{"text": "And Collins ( 2000 ) argues for `` keeping track of counts of arbitrary fragments within parse trees '' , which has indeed been carried out in Collins and Duffy ( 2002 ) who use exactly the same set of ( all ) tree fragments as proposed in Bod ( 1992 ) .", "citing_paper_id": "E03-1005", "cited_paper_id": "P02-1034", "citing_paper_year": 2003, "cited_paper_year": 2002, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "new ranking algorithms for parsing and tagging kernels over discrete structures and the voted perceptron", "cited_author_ids": ["M Collins", "N Duffy"], "citing_author_ids": null, "extended_context": "The importance of including nonheadwords has become uncontroversial ( e.g. Collins 1999 ; Charniak 2000 ; Goodman 1998 ) . And Collins ( 2000 ) argues for `` keeping track of counts of arbitrary fragments within parse trees '' , which has indeed been carried out in Collins and Duffy ( 2002 ) who use exactly the same set of ( all ) tree fragments as proposed in Bod ( 1992 ) . 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{"text": "In our work , we gather sets of sentences , and assume ( but do not employ ) existing approaches for their organization ( Goldstein et al. 2000 ; Barzilay , Elhadad , and McKeown 2001 ; Barzilay and McKeown 2005 ) .", "citing_paper_id": "J09-4010", "cited_paper_id": "J05-3002", "citing_paper_year": 2009, "cited_paper_year": 2005, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "sentence fusion for multidocument news summarization", "cited_author_ids": ["R Barzilay", "K R McKeown"], "citing_author_ids": null, "extended_context": "Unlike a document reuse approach , sentence-level approaches need to consider issues of discourse coherence in order to ensure that the extracted combination of sentences is coherent or at least understandable . In our work , we gather sets of sentences , and assume ( but do not employ ) existing approaches for their organization ( Goldstein et al. 2000 ; Barzilay , Elhadad , and McKeown 2001 ; Barzilay and McKeown 2005 ) . The appeal of a sentence-level approach is that it supports the generation of a `` combination response '' in situations where there is insufficient evidence for a single document containing a full response , but there is enough evidence for parts of responses .", "section_number": 3, "section_title": null, "intent": "Background", "cite_marker_offset": [186, 211], "sents_before": [[{"index": 1, "word": "In", "lemma": "in", "after": " ", "pos": "IN", "characterOffsetEnd": 577, "segment_span": [0, 11], "characterOffsetBegin": 575, "originalText": "In", "ArgType": null, "before": " "}, {"index": 2, "word": "our", "lemma": "our", "after": " ", "pos": "PRP$", "characterOffsetEnd": 581, "segment_span": [0, 11], "characterOffsetBegin": 578, "originalText": "our", "ArgType": null, "before": " "}, {"index": 3, "word": "work", "lemma": "work", "after": "", "pos": "NN", "characterOffsetEnd": 586, "segment_span": [0, 11], "characterOffsetBegin": 582, "originalText": "work", "ArgType": null, 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{"text": "criteria and data used in our experiments are based on the work of Talbot et al. ( 2011 ) .", "citing_paper_id": "D11-1138", "cited_paper_id": "W11-2102", "citing_paper_year": 2011, "cited_paper_year": 2011, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "a lightweight evaluation framework for machine translation reordering", "cited_author_ids": ["D Talbot", "H Kazawa", "H Ichikawa", "J Katz-Brown", "M Seno", "F Och"], "citing_author_ids": null, "extended_context": "1Our rules are similar to those from Xu et al. ( 2009 ) . criteria and data used in our experiments are based on the work of Talbot et al. ( 2011 ) . 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{"text": "We present experiments on the two standard coreference resolution datasets , ACE-2004 ( NIST , 2004 ) and OntoNotes-5 .0 ( Hovy et al. , 2006 ) .", "citing_paper_id": "K15-1002", "cited_paper_id": "N06-2015", "citing_paper_year": 2015, "cited_paper_year": 2006, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "ontonotes the 90 solution", "cited_author_ids": ["E Hovy", "M Marcus", "M Palmer", "L Ramshaw", "R Weischedel"], "citing_author_ids": null, "extended_context": "We present experiments on the two standard coreference resolution datasets , ACE-2004 ( NIST , 2004 ) and OntoNotes-5 .0 ( Hovy et al. , 2006 ) . Our approach results in a substantial reduction in the coreference performance gap between gold and predicted mentions , and significantly outperforms existing stat-of-the-art results on coreference resolution ; in addition , it achieves significant performance improvement on MD for both datasets .", "section_number": 4, "section_title": null, "intent": "Uses", "cite_marker_offset": [123, 141], "sents_before": [[{"index": 1, "word": "We", "lemma": "we", "after": " ", "pos": "PRP", "characterOffsetEnd": 2, "segment_span": [0, 27], "characterOffsetBegin": 0, "originalText": "We", "ArgType": "subj", "before": ""}, {"index": 2, "word": "present", "characterOffsetEnd": 10, "after": " ", "pos": "VBP", "is_root": true, "lemma": "present", "segment_span": [0, 27], "tense": "P", "characterOffsetBegin": 3, "originalText": "present", "ArgType": "verb", "before": " "}, {"index": 3, "word": "experiments", "lemma": "experiment", "after": " ", "pos": "NNS", "characterOffsetEnd": 22, "segment_span": 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{"text": "• Only qualitative observations of the responses were reported ( no formal evaluation was performed ) ( Lapalme and Kosseim 2003 ; Roy and Subramaniam 2006 ) .", "citing_paper_id": "J09-4010", "cited_paper_id": "P06-1093", "citing_paper_year": 2009, "cited_paper_year": 2006, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "automatic generation of domain models for callcenters from noisy transcriptions", "cited_author_ids": ["S Roy", "L V Subramaniam"], "citing_author_ids": null, "extended_context": "These systems addressed the evaluation issue as follows . • Only qualitative observations of the responses were reported ( no formal evaluation was performed ) ( Lapalme and Kosseim 2003 ; Roy and Subramaniam 2006 ) . • Only an automatic evaluation was performed , which relied on having model responses ( Berger and Mittal 2000 ; Berger et al. 2000 ) .", "section_number": 3, "section_title": null, "intent": "CompareOrContrast", 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{"text": "And subderivations headed by A1 with external nonterminals only at the leaves , internal nonterminals elsewhere , have probability 1/a1 ( Goodman 1996 ) .", "citing_paper_id": "E03-1005", "cited_paper_id": "External_16080", "citing_paper_year": 2003, "cited_paper_year": 1996, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "efficient algorithms for parsing the dop model", "cited_author_ids": ["J Goodman"], "citing_author_ids": null, "extended_context": "Goodman then shows by simple induction that subderivations headed by A with external nonterminals at the roots and leaves , internal nonterminals elsewhere have probability 1/a . And subderivations headed by A1 with external nonterminals only at the leaves , internal nonterminals elsewhere , have probability 1/a1 ( Goodman 1996 ) . 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{"text": "Hohensee and Bender ( 2012 ) have conducted a study on dependency parsing for 21 languages using features that encode whether the values for certain attributes are equal or not for a node and its governor .", "citing_paper_id": "J13-1008", "cited_paper_id": "N12-1032", "citing_paper_year": 2013, "cited_paper_year": 2012, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "getting more from morphology in multilingual dependency parsing", "cited_author_ids": ["Matt Hohensee", "Emily M Bender"], "citing_author_ids": null, "extended_context": "Furthermore , we demonstrate that our results carry over successfully to another parser , the Easy-First Parser ( Goldberg and Elhadad 2010 ) ( Section 6 ) . Hohensee and Bender ( 2012 ) have conducted a study on dependency parsing for 21 languages using features that encode whether the values for certain attributes are equal or not for a node and its governor . These features are potentially powerful , because they generalize to the very notion of agreement , away from the specific values of the attributes on which agreement occurs .9 We expect this kind of feature to yield lower gains for Arabic , unless :", "section_number": 3, "section_title": null, "intent": "Background", "cite_marker_offset": [0, 28], "sents_before": [[{"index": 1, "word": "Hohensee", "lemma": "Hohensee", "after": " ", "pos": "NNP", "characterOffsetEnd": 1862, "segment_span": [0, 18], "characterOffsetBegin": 1854, "originalText": "Hohensee", "ArgType": "subj", "before": " "}, {"index": 2, "word": "and", "lemma": "and", "after": " ", "pos": "CC", "characterOffsetEnd": 1866, "segment_span": [0, 18], "characterOffsetBegin": 1863, "originalText": "and", "ArgType": null, "before": " "}, {"index": 3, "word": "Bender", "lemma": "Bender", "after": " ", "pos": "NNP", "characterOffsetEnd": 1873, "segment_span": [0, 18], "characterOffsetBegin": 1867, "originalText": "Bender", 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{"text": "The relation between discourse and prosodic phrasing has been examined in some detail by Bing ( 1985 ) , who argues that each noun phrase in an utterance constitutes a separate prosodic phrase unless it is destressed because of reference to previous discourse .", "citing_paper_id": "J90-3003", "cited_paper_id": "External_73668", "citing_paper_year": 1990, "cited_paper_year": 1985, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "aspects of prosody", "cited_author_ids": ["J Bing"], "citing_author_ids": null, "extended_context": "f. Two years II have passed since then . The relation between discourse and prosodic phrasing has been examined in some detail by Bing ( 1985 ) , who argues that each noun phrase in an utterance constitutes a separate prosodic phrase unless it is destressed because of reference to previous discourse . Bing also observes that constituents that refer to items newly introduced into a discourse tend to be longer .", "section_number": 1, "section_title": null, "intent": "Background", "cite_marker_offset": [89, 102], "sents_before": [[{"index": 1, "word": "The", "lemma": "the", "after": " ", "pos": "DT", "characterOffsetEnd": 43, "segment_span": [0, 19], "characterOffsetBegin": 40, "originalText": "The", "ArgType": null, "before": " "}, {"index": 2, "word": "relation", "lemma": "relation", "after": " ", "pos": "NN", "characterOffsetEnd": 52, "segment_span": [0, 19], "characterOffsetBegin": 44, "originalText": "relation", "ArgType": null, "before": " "}, {"index": 3, "word": "between", "lemma": "between", "after": " ", "pos": "IN", "characterOffsetEnd": 60, "segment_span": [0, 19], "characterOffsetBegin": 53, "originalText": "between", "ArgType": null, "before": " "}, {"index": 4, "word": "discourse", "lemma": "discourse", "after": " ", "pos": "NN", "characterOffsetEnd": 70, 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{"text": "By contrast , Turkish ( Oflazer et al. , 2003 ; Atalay et al. , 2003 ) exhibits high root accuracy but consistently low attachment scores ( about 88 % for length 1 and 68 % for length 2 ) .", "citing_paper_id": "W06-2933", "cited_paper_id": "External_6725", "citing_paper_year": 2006, "cited_paper_year": 2003, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "the annotation process in the turkish treebank", "cited_author_ids": ["N B Atalay", "K Oflazer", "B Say"], "citing_author_ids": null, "extended_context": "as well as a rapid degradation of attachment score with arc length ( from about 93 % for length 1 to 67 % for length 2 ) . By contrast , Turkish ( Oflazer et al. , 2003 ; Atalay et al. , 2003 ) exhibits high root accuracy but consistently low attachment scores ( about 88 % for length 1 and 68 % for length 2 ) . 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{"text": "The candidate examples that lead to the most disagreements among the different learners are considered to have the highest TUV ( Cohn , Atlas , and Ladner 1994 ; Freund et al. 1997 ) .", "citing_paper_id": "J04-3001", "cited_paper_id": "External_15318", "citing_paper_year": 2004, "cited_paper_year": 1997, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "selective sampling using the query by committee algorithm", "cited_author_ids": ["Yoav Freund", "H Sebastian Seung", "Eli Shamir", "Naftali Tishby"], "citing_author_ids": null, "extended_context": "A committee-based selection algorithm works with multiple learners , each maintaining a different hypothesis ( perhaps pertaining to different aspects of the problem ) . The candidate examples that lead to the most disagreements among the different learners are considered to have the highest TUV ( Cohn , Atlas , and Ladner 1994 ; Freund et al. 1997 ) . 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{"text": "Subsequently , we extracted the bilingual phrase table from the aligned corpora using the Moses toolkit ( Koehn et al. , 2007 ) .", "citing_paper_id": "P11-1134", "cited_paper_id": "External_4216", "citing_paper_year": 2011, "cited_paper_year": 2007, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "moses open source toolkit for statistical machine translation", "cited_author_ids": ["Philipp Koehn", "Hieu Hoang", "Alexandra Birch", "Chris Callison-Burch", "Marcello Federico", "Nicola Bertoldi", "Brooke Cowan", "Wade Shen"], "citing_author_ids": null, "extended_context": "We run TreeTagger ( Schmid , 1994 ) for tokenization , and used the Giza + + ( Och and Ney , 2003 ) to align the tokenized corpora at the word level . Subsequently , we extracted the bilingual phrase table from the aligned corpora using the Moses toolkit ( Koehn et al. , 2007 ) . 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{"text": "Representative systems are described in Boisen et al. ( 1989 ) , De Mattia and Giachin ( 1989 ) , Niedermair ( 1989 ) , Niemann ( 1990 ) , and Young ( 1989 ) .", "citing_paper_id": "J92-1004", "cited_paper_id": "H89-1017", "citing_paper_year": 1992, "cited_paper_year": 1989, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "the minds system using context and dialog to enhance speech recognitionquot", "cited_author_ids": ["S R Young"], "citing_author_ids": null, "extended_context": "Current advances in research and development of spoken language systems2 can be found , for example , in the proceedings of the DARPA speech and natural language workshops , as well as in publications from participants of the ESPRIT SUNDIAL project . Representative systems are described in Boisen et al. ( 1989 ) , De Mattia and Giachin ( 1989 ) , Niedermair ( 1989 ) , Niemann ( 1990 ) , and Young ( 1989 ) . * Spoken Language Systems Group , Laboratoiy for Computer Science , MIT , Cambridge MA 02139 f This research was supported by DARPA under Contract N00014-89 +1332 , monitored through the Office of Naval Research .", "section_number": 1, "section_title": null, "intent": "Background", "cite_marker_offset": [143, 157], "sents_before": [[{"index": 1, "word": "Representative", "lemma": "Representative", "after": " ", "pos": "NNP", "characterOffsetEnd": 1016, "segment_span": [0, 35], "characterOffsetBegin": 1002, "originalText": "Representative", "ArgType": null, "before": " "}, {"index": 2, "word": "systems", "lemma": "system", "after": " ", "pos": "NNS", "characterOffsetEnd": 1024, "segment_span": [0, 35], "characterOffsetBegin": 1017, "originalText": "systems", "ArgType": null, "before": " "}, {"index": 3, "word": "are", "lemma": "be", "after": " ", "pos": "VBP", "characterOffsetEnd": 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{"text": "As a generalization , Briscoe ( 2001 ) notes that lexicons such as COMLEX tend to demonstrate high precision but low recall .", "citing_paper_id": "J05-3003", "cited_paper_id": "External_59044", "citing_paper_year": 2005, "cited_paper_year": 2001, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "from dictionary to corpus to selforganizing dictionary learning valency associations in the face of variation and change", "cited_author_ids": ["Edward Briscoe"], "citing_author_ids": null, "extended_context": "which is bound to be less certain than the assignment of frames based entirely on existing examples . As a generalization , Briscoe ( 2001 ) notes that lexicons such as COMLEX tend to demonstrate high precision but low recall . 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{"text": "Such systems extract information from some types of syntactic units ( clauses in ( Fillmore and Atkins , 1998 ; Gildea and Jurafsky , 2002 ; Hull and Gomez , 1996 ) ; noun phrases in ( Hull and Gomez , 1996 ; Rosario et al. , 2002 ) ) .", "citing_paper_id": "W06-3813", "cited_paper_id": "External_9163", "citing_paper_year": 2006, "cited_paper_year": 1996, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "semantic interpretation of nominalizations", "cited_author_ids": ["Richard D Hull", "Fernando Gomez"], "citing_author_ids": null, "extended_context": "In other methods , lexical resources are specifically tailored to meet the requirements of the domain ( Rosario and Hearst , 2001 ) or the system ( Gomez , 1998 ) . Such systems extract information from some types of syntactic units ( clauses in ( Fillmore and Atkins , 1998 ; Gildea and Jurafsky , 2002 ; Hull and Gomez , 1996 ) ; noun phrases in ( Hull and Gomez , 1996 ; Rosario et al. , 2002 ) ) . 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{"text": "Various approaches for computing semantic relatedness of words or concepts have been proposed , e.g. dictionary-based ( Lesk , 1986 ) , ontology-based ( Wu and Palmer , 1994 ; Leacock and Chodorow , 1998 ) , information-based ( Resnik , 1995 ; Jiang and Conrath , 1997 ) or distributional ( Weeds and Weir , 2005 ) .", "citing_paper_id": "W06-1104", "cited_paper_id": "External_933", "citing_paper_year": 2006, "cited_paper_year": 1997, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "semantic similarity based on corpus statistics and lexical taxonomy", "cited_author_ids": ["Jay J Jiang", "David W Conrath"], "citing_author_ids": null, "extended_context": "Various approaches for computing semantic relatedness of words or concepts have been proposed , e.g. dictionary-based ( Lesk , 1986 ) , ontology-based ( Wu and Palmer , 1994 ; Leacock and Chodorow , 1998 ) , information-based ( Resnik , 1995 ; Jiang and Conrath , 1997 ) or distributional ( Weeds and Weir , 2005 ) . The knowledge sources used for computing relatedness can be as different as dictionaries , ontologies or large corpora .", "section_number": 3, "section_title": null, "intent": "Background", "cite_marker_offset": [244, 268], "sents_before": [[{"index": 1, "word": "Various", "lemma": "various", "after": " ", "pos": "JJ", "characterOffsetEnd": 7, "segment_span": [0, 58], "characterOffsetBegin": 0, "originalText": "Various", "ArgType": null, "before": ""}, {"index": 2, "word": "approaches", "lemma": "approach", "after": " ", "pos": "NNS", "characterOffsetEnd": 18, "segment_span": [0, 58], "characterOffsetBegin": 8, "originalText": "approaches", "ArgType": null, "before": " "}, {"index": 3, "word": "for", "lemma": "for", "after": " ", "pos": "IN", "characterOffsetEnd": 22, "segment_span": [0, 58], "characterOffsetBegin": 19, "originalText": "for", "ArgType": null, "before": " "}, {"index": 4, "word": "computing", "lemma": "compute", "after": " ", "pos": "VBG", "characterOffsetEnd": 32, 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{"text": "Besides WordNet , the RTE literature documents the use of a variety of lexical information sources ( Bentivogli et al. , 2010 ; Dagan et al. , 2009 ) .", "citing_paper_id": "P11-1134", "cited_paper_id": "External_14644", "citing_paper_year": 2011, "cited_paper_year": 2009, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "recognizing textual entailment rational evaluation and approaches", "cited_author_ids": ["Ido Dagan", "Bill Dolan", "Bernardo Magnini", "Dan Roth"], "citing_author_ids": null, "extended_context": "Paths between concepts and glosses can be used to calculate similarity/relatedness scores between single words , that contribute to the computation of the overall similarity between the text and the hypothesis . Besides WordNet , the RTE literature documents the use of a variety of lexical information sources ( Bentivogli et al. , 2010 ; Dagan et al. , 2009 ) . 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{"text": "The question answering system developed by Chu-Carroll et al. ( 2003 ) belongs to the merging category of approaches , where the output of an individual method can be used as input to a different method ( this corresponds to Burke 's cascade sub-category ) .", "citing_paper_id": "J09-4010", "cited_paper_id": "N03-1004", "citing_paper_year": 2009, "cited_paper_year": 2003, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "in question answering two heads are better than one", "cited_author_ids": ["J Chu-Carroll", "K Czuba", "J M Prager", "A Ittycheriah"], "citing_author_ids": null, "extended_context": "Instead it uses a voting mechanism to select the answer given by the majority of methods . The question answering system developed by Chu-Carroll et al. 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{"text": "More recently , ( Sebastiani , 2002 ) has performed a good survey of document categorization ; recent works can also be found in ( Joachims , 2002 ) , ( Crammer and Singer , 2003 ) , and ( Lewis et al. , 2004 ) .", "citing_paper_id": "W04-1610", "cited_paper_id": "External_87687", "citing_paper_year": 2004, "cited_paper_year": 2003, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "a family of additive online algorithms for category ranking”", "cited_author_ids": ["K Crammer", "Y Singer"], "citing_author_ids": null, "extended_context": "A good study comparing document categorization algorithms can be found in ( Yang and Liu , 1999 ) . More recently , ( Sebastiani , 2002 ) has performed a good survey of document categorization ; recent works can also be found in ( Joachims , 2002 ) , ( Crammer and Singer , 2003 ) , and ( Lewis et al. , 2004 ) . Concerning Arabic , one automatic categorizer has been reported to have been put under operational use to classify Arabic documents ; it is referred to as `` Sakhr 's categorizer '' ( Sakhr , 2004 ) .", "section_number": 3, "section_title": null, "intent": "Background", "cite_marker_offset": [153, 178], "sents_before": [[{"index": 1, "word": "More", "lemma": "more", "after": " ", "pos": "RBR", "characterOffsetEnd": 640, "segment_span": [0, 17], "characterOffsetBegin": 636, "originalText": "More", "ArgType": null, "before": " "}, {"index": 2, "word": "recently", "lemma": "recently", "after": "", "pos": "RB", "characterOffsetEnd": 649, "segment_span": [0, 17], "characterOffsetBegin": 641, "originalText": "recently", "ArgType": null, "before": " "}, {"index": 3, "word": ",", "lemma": ",", "after": " ", "pos": ",", "characterOffsetEnd": 650, "segment_span": [0, 17], "characterOffsetBegin": 649, "originalText": ",", "ArgType": null, "before": ""}, {"index": 4, "word": "(", "lemma": "-lrb-", 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{"text": "Discriminant analysis has been employed by researchers in automatic text genre detection ( Biber 1993b ; Karlgren and Cutting 1994 ) since it offers a simple and robust solution despite the fact that it presupposes normal distributions of the discriminating variables .", "citing_paper_id": "J00-4001", "cited_paper_id": "External_30353", "citing_paper_year": 2000, "cited_paper_year": 1993, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "using registerdiversified corpora for general language studies", "cited_author_ids": ["Douglas Biber"], "citing_author_ids": null, "extended_context": "where C , is the covariance matrix of x. Using this classification method we can also derive the probability that a case belongs to a particular group ( i.e. , posterior probabilities ) , which is roughly proportional to the Mahalanobis distance from that group centroid . 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{"text": "This model has previously been shown to provide excellent performance on multiple tasks , including prediction of association norms , word substitution errors , semantic inferences , and word similarity ( Andrews et al. , 2009 ; Silberer and Lapata , 2012 ) .", "citing_paper_id": "D13-1115", "cited_paper_id": "External_32478", "citing_paper_year": 2013, "cited_paper_year": 2009, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "integrating experiential and distributional data to learn semantic representations", "cited_author_ids": ["Mark Andrews", "Gabriella Vigliocco", "David Vinson"], "citing_author_ids": null, "extended_context": "Andrews et al. ( 2009 ) and is based on a generalization of Latent Dirichlet Allocation . This model has previously been shown to provide excellent performance on multiple tasks , including prediction of association norms , word substitution errors , semantic inferences , and word similarity ( Andrews et al. , 2009 ; Silberer and Lapata , 2012 ) . While prior work has used the model only with feature norms and visual attributes , we show that low-level image features are directly compatible with the model and provide improved representations of word meaning .", "section_number": 2, "section_title": null, "intent": "Extends", "cite_marker_offset": [205, 226], "sents_before": [[{"index": 1, "word": "This", "lemma": "this", "after": " ", "pos": "DT", "characterOffsetEnd": 91, "segment_span": [0, 43], "characterOffsetBegin": 87, "originalText": "This", "ArgType": null, "before": " "}, {"index": 2, "word": "model", "lemma": "model", "after": " ", "pos": "NN", "characterOffsetEnd": 97, "segment_span": [0, 43], "characterOffsetBegin": 92, "originalText": "model", "ArgType": null, "before": " "}, {"index": 3, "word": "has", "lemma": "have", "after": " ", "pos": "VBZ", "characterOffsetEnd": 101, "segment_span": [0, 43], "characterOffsetBegin": 98, "originalText": "has", "ArgType": null, "before": " "}, {"index": 4, "word": "previously", 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{"text": "In other words , existing treatments of gradables in GRE fail to take the `` efficiency of language '' into account ( Barwise and Perry 1983 ; see our Section 2 ) .", "citing_paper_id": "J06-2002", "cited_paper_id": "External_522", "citing_paper_year": 2006, "cited_paper_year": 1983, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "situations and attitudes", "cited_author_ids": ["Jon Barwise", "John Perry"], "citing_author_ids": null, "extended_context": "Then IA would tend to have little use for this property at all since , presumably , every chihuahua would be small and every alsatian large , making each of the combinations -LCB- large , chihuahua -RCB- ( which denotes the empty set ) and -LCB- large , alsatian -RCB- ( the set of all alsatians ) useless . 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{"text": "Word alignments are used primarily for extracting minimal translation units for machine translation ( MT ) ( e.g. , phrases [ Koehn , Och , and Marcu 2003 ] and rules [ Galley et al. 2004 ; Chiang et al. 2005 ] ) as well as for", "citing_paper_id": "J10-3007", "cited_paper_id": "N04-1035", "citing_paper_year": 2010, "cited_paper_year": 2004, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "what’s in a translation rule", "cited_author_ids": ["Michel Galley", "Mark Hopkins", "Kevin Knight", "Daniel Marcu"], "citing_author_ids": null, "extended_context": "Although no longer competitive as end-to-end translation models , the IBM Models , as well as the hidden Markov model ( HMM ) of Vogel , Ney , and Tillmann ( 1996 ) , are still widely used for word alignment . Word alignments are used primarily for extracting minimal translation units for machine translation ( MT ) ( e.g. , phrases [ Koehn , Och , and Marcu 2003 ] and rules [ Galley et al. 2004 ; Chiang et al. 2005 ] ) as well as for MT system combination ( Matusov , Ueffing , and Ney 2006 ) .", "section_number": 1, "section_title": null, "intent": "Background", "cite_marker_offset": [169, 187], "sents_before": [[{"index": 1, "word": "Word", "lemma": "word", "after": " ", "pos": "NN", "characterOffsetEnd": 451, "segment_span": [0, 5], "characterOffsetBegin": 447, "originalText": "Word", "ArgType": null, "before": " "}, {"index": 2, "word": "alignments", "lemma": "alignment", "after": " ", "pos": "NNS", "characterOffsetEnd": 462, "segment_span": [0, 5], "characterOffsetBegin": 452, "originalText": "alignments", "ArgType": null, "before": " "}, {"index": 3, "word": "are", "lemma": "be", "after": " ", "pos": "VBP", "characterOffsetEnd": 466, "segment_span": [0, 5], "characterOffsetBegin": 463, 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Kaplan and Bresnan 1982 ; @@CITATION ; Dalrymple 2001 ] , head-driven phrase structure grammar [ HPSG ] [ Pollard and Sag 1994 ] , tree-adjoining grammar [ TAG ] [ Joshi 1988 ] , and combinatory categorial grammar [ CCG ] [ Ades and Steedman 1982 ] ) , the lexicon is the central repository for much morphological , syntactic , and semantic information .", "citation_id": "J05-3003_5", "citation_excerpt_index": 0, "section_name": "introduction"}
{"text": "We have shown elsewhere ( Jensen and Binot 1988 ; Zadrozny 1987a , 1987b ) that natural language programs , such as on-line grammars and dictionaries , can be used as referential levels for commonsense reasoning -- for example , to disambiguate PP attachment .", "citing_paper_id": "J91-2003", "cited_paper_id": "External_76184", "citing_paper_year": 1991, "cited_paper_year": 1987, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "intended models circumscription and commonsense reasoningquot", "cited_author_ids": ["W Zadrozny"], "citing_author_ids": null, "extended_context": "Gricean maxims belong there ; Section 6 will be devoted to a presentation of the metalevel rules corresponding to them . We have shown elsewhere ( Jensen and Binot 1988 ; Zadrozny 1987a , 1987b ) that natural language programs , such as on-line grammars and dictionaries , can be used as referential levels for commonsense reasoning -- for example , to disambiguate PP attachment . This means that information contained in grammars and dictionaries can be used to constrain possible interpretations of the logical predicates of an object-level theory .", "section_number": 1, "section_title": null, "intent": "Extends", "cite_marker_offset": [50, 63], "sents_before": [[{"index": 1, "word": "We", "lemma": "we", "after": " ", "pos": "PRP", "characterOffsetEnd": 2, "segment_span": [0, 40], "characterOffsetBegin": 0, "originalText": "We", "ArgType": "subj", "before": ""}, {"index": 2, "word": "have", "lemma": "have", "after": " ", "pos": "VBP", "characterOffsetEnd": 7, "segment_span": [0, 40], "characterOffsetBegin": 3, "originalText": "have", "ArgType": null, "before": " "}, {"index": 3, "word": "shown", "characterOffsetEnd": 13, "after": " ", "pos": "VBN", "is_root": true, "lemma": "show", "segment_span": [0, 40], "tense": "N", "characterOffsetBegin": 8, "originalText": "shown", "has_aux": true, "ArgType": "verb", "before": " "}, {"index": 4, "word": "elsewhere", 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{"text": "Thus rather than a single training procedure , we can actually partition the examples by predicate , and train a 1For a fixed verb , MI is proportional to Keller and Lapata ( 2003 ) 's conditional probability scores for pseudodisambiguation of ( v , n , n ′ ) triples : Pr ( v | n ) = Pr ( v , n ) / Pr ( n ) , which was shown to be a better measure of association than co-occurrence frequency f ( v , n ) .", "citing_paper_id": "D08-1007", "cited_paper_id": "J03-3005", "citing_paper_year": 2008, "cited_paper_year": 2003, "citing_paper_title": "a holistic lexiconbased approach to opinion mining", "cited_paper_title": "using the web to obtain frequencies for unseen bigrams", "cited_author_ids": ["Frank Keller", "Mirella Lapata"], "citing_author_ids": null, "extended_context": "In this representation , features for one predicate will be completely independent from those for every other predicate . Thus rather than a single training procedure , we can actually partition the examples by predicate , and train a 1For a fixed verb , MI is proportional to Keller and Lapata ( 2003 ) 's conditional probability scores for pseudodisambiguation of ( v , n , n ′ ) triples : Pr ( v | n ) = Pr ( v , n ) / Pr ( n ) , which was shown to be a better measure of association than co-occurrence frequency f ( v , n ) . Normalizing by Pr ( v ) ( yielding MI ) allows us to use a constant threshold across all verbs .", "section_number": 4, "section_title": null, "intent": "Motivation", "cite_marker_offset": [155, 181], "sents_before": [[{"index": 1, "word": "Thus", "lemma": "thus", "after": " ", "pos": "RB", "characterOffsetEnd": 869, "segment_span": [0, 19], "characterOffsetBegin": 865, "originalText": "Thus", "ArgType": null, "before": " "}, {"index": 2, "word": "rather", "lemma": "rather", "after": " ", "pos": "RB", "characterOffsetEnd": 876, "segment_span": [0, 19], "characterOffsetBegin": 870, "originalText": "rather", "ArgType": null, "before": " "}, {"index": 3, "word": "than", "lemma": "than", "after": " ", "pos": "IN", "characterOffsetEnd": 881, "segment_span": [0, 19], "characterOffsetBegin": 877, "originalText": "than", "ArgType": null, "before": " "}, {"index": 4, "word": "a", "lemma": "a", "after": " ", "pos": "DT", "characterOffsetEnd": 883, "segment_span": [0, 19], "characterOffsetBegin": 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