should corpora texts be gold standards for nlg

FOG does not appear to have generic rules governing the use of gradable notions : it does not compute the meaning of a vague term based on the context , but uses fixed boundary values instead . A more flexible approach is used by Reiter and Sripada ( 2002 ) , where users can specify boundary values for attributes like rainfall , specifying , for example , rain counts as moderate above 7 mm/h , as heavy above 20 mm/h , and so on . A third approach was implemented in Dial Your Disc ( DYD ) , where the extension of a gradable adjective like famous was computed rather than specified by hand ( van Deemter and Odijk 1997 ) .

A more flexible approach is used by @@CITATION , where users can specify boundary values for attributes like rainfall , specifying , for example , rain counts as moderate above 7 mm/h , as heavy above 20 mm/h , and so on .


a holistic lexiconbased approach to opinion mining

paradise a framework for evaluating spoken dialogue agents

Marilyn A Walker
Diane J Litman
Candance A Kamm
Alicia Abella

User satisfaction was assessed by asking the subjects to fill out a questionnaire after interacting with each version of the system . Furthermore , a number of performance features , largely based on the PARADISE dialogue evaluation scheme ( Walker et al. , 1997 ) , were automatically logged , derived , or manually annotated . In addition , we logged the cues automatically detected in each user utterance , as well as the initiative distribution for each turn and the dialogue acts selected to generate each system response .

Furthermore , a number of performance features , largely based on the PARADISE dialogue evaluation scheme ( @@CITATION ) , were automatically logged , derived , or manually annotated .


If neither order appears in the training data , then neither a b nor b a and an order must be randomly assigned . Shaw and Hatzivassiloglou ( 1999 ) propose to generalize the direct evidence method so that it can apply to unseen pairs of adjectives by computing the transitive closure of the ordering relation . That is , if a c and c b , we can conclude that a b. To take an example from the BNC , the adjectives large and green never occur together in the training data , and so would be assigned a random order by the direct evidence method .

@@CITATION propose to generalize the direct evidence method so that it can apply to unseen pairs of adjectives by computing the transitive closure of the ordering relation .


bleu a method for automatic evaluation of machine translation

Kishore Papineni
Salim Roukos
Todd Ward
WeiJing Zhu

We evaluated our translations with IBM 's BLEU evaluation metric ( Papineni et al. , 2001 ) , using the same evaluation method and reference retranslations that were used for evaluation at HLT Workshop 2002 at CLSP ( Haji 6 et al. , 2002 ) . We used four reference retranslations of 490 sentences selected from the WSJ sections 22 , 23 , and 24 , which were themselves used as the fifth reference .

We evaluated our translations with IBM 's BLEU evaluation metric ( @@CITATION ) , using the same evaluation method and reference retranslations that were used for evaluation at HLT Workshop 2002 at CLSP ( Haji 6 et al. , 2002 ) .


deterministic partofspeech tagging with finitestate transducers

An example of this is the estimation of maximum entropy models , from simple iterative estimation algorithms used by Ratnaparkhi ( 1998 ) that converge very slowly , to complex techniques from the optimisation literature that converge much more rapidly ( Malouf , 2002 ) . Other attempts to address efficiency include the fast Transformation Based Learning ( TBL ) Toolkit ( Ngai and Florian , 2001 ) which dramatically speeds up training TBL systems , and the translation of TBL rules into finite state machines for very fast tagging ( Roche and Schabes , 1997 ) . The TNT POS tagger ( Brants , 2000 ) has also been designed to train and run very quickly , tagging between 30,000 and 60,000 words per second .

Other attempts to address efficiency include the fast Transformation Based Learning ( TBL ) Toolkit ( Ngai and Florian , 2001 ) which dramatically speeds up training TBL systems , and the translation of TBL rules into finite state machines for very fast tagging ( @@CITATION ) .


simple robust scalable semisupervised learning via expectation regularization

Such a statement is data-dependent in the sense that if the model satisfies the constraints then we do not need to change it ; if it is far from satisfying it we might need to make very dramatic changes . PR is closely related to the work of Mann and McCallum ( 2007 , 2008 ) , who concurrently developed the idea of using penalties based on posterior expectations of features to guide semi-supervised learning . They call their method generalized expectation ( GE ) constraints or alternatively expectation regularization .

PR is closely related to the work of @@CITATION , 2008 ) , who concurrently developed the idea of using penalties based on posterior expectations of features to guide semi-supervised learning .


We experimented with various Weka classifiers , comprising Hidden Naive Bayes , SMO , ID3 , LADTree and Decision Table . The best results on most of our data were obtained using Hidden Naive Bayes ( HNB ) ( Zhang et al. , 2005 ) . Therefore , here we show the results of this classifier .

The best results on most of our data were obtained using Hidden Naive Bayes ( HNB ) ( @@CITATION ) .


nphil.uni-tuebingen . de URL : http://www.sfs.nphil.uni-tuebingen.de/sfb / b4home.html 1 This is , for example , the case for all proposals working with verbal lexical entries that raise the arguments of a verbal complement ( Hinrichs and Nakazawa 1989 ) that also use lexical rules such as the Complement Extraction Lexical Rule ( Pollard and Sag 1994 ) or the Complement Cliticization Lexical Rule ( Miller and Sag 1993 ) to operate on those raised elements . Also an analysis treating adjunct extraction via lexical rules ( van Noord and Bouma 1994 ) results in an infinite lexicon .

de URL : http://www.sfs.nphil.uni-tuebingen.de/sfb / b4home.html 1 This is , for example , the case for all proposals working with verbal lexical entries that raise the arguments of a verbal complement ( Hinrichs and Nakazawa 1989 ) that also use lexical rules such as the Complement Extraction Lexical Rule ( @@CITATION ) or the Complement Cliticization Lexical Rule ( Miller and Sag 1993 ) to operate on those raised elements .


pronoun resolution the practical alternative presented at the discourse anaphora and anaphor resolution colloquium daarc1

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 . A number of proposals in the 1990s deliberately limited the extent to which they relied on domain and/or linguistic knowledge and reported promising results in knowledge-poor operational environments ( Dagan and Itai 1990 , 1991 ; Lappin and Leass 1994 ; Nasukawa 1994 ; Kennedy and Boguraev 1996 ; Williams , Harvey , and Preston 1996 ; Baldwin 1997 ; Mitkov 1996 , 1998b ) . The drive toward knowledge-poor and robust approaches was further motivated by the emergence of cheaper and more reliable corpus-based NLP tools such as partof-speech taggers and shallow parsers , alongside the increasing availability of corpora and other NLP resources ( e.g. , ontologies ) .

A number of proposals in the 1990s deliberately limited the extent to which they relied on domain and/or linguistic knowledge and reported promising results in knowledge-poor operational environments ( Dagan and Itai 1990 , 1991 ; Lappin and Leass 1994 ; Nasukawa 1994 ; Kennedy and Boguraev 1996 ; Williams , Harvey , and Preston 1996 ; Baldwin 1997 ; @@CITATION , 1998b ) .


using partofspeech and semantic tagging for the corpusbased learning of qualia structure elements

Pierrette Bouillon
Vincent Claveau
Cecile Fabre
Pascale Sebillot

extraction of N-V pairs from the corpus with the inferred patterns . ASARES has been previously applied to the acquisition of word pairs sharing semantic relations defined in the Generative Lexicon framework ( Pustejovsky , 1995 ) and called qualia relations ( Bouillon et al. , 2001 ) . Here , we propose to use ASARES in a quite similar way to retrieve our valid N-V pairs .

ASARES has been previously applied to the acquisition of word pairs sharing semantic relations defined in the Generative Lexicon framework ( Pustejovsky , 1995 ) and called qualia relations ( @@CITATION ) .


cascading collective classification for bridging anaphora recognition using a rich linguistic feature set

All rules from the rule-based system are incorporated into mlSystem ruleFeats as the features . mlSystem ruleFeats + atomFeats We augment mlSystem ruleFeats with more features from our previous work ( Markert et al. , 2012 ; Hou et al. , 2013a ; Hou et al. , 2013b ) on bridging anaphora recognition and antecedent selection . Some of these features overlap with the atomic features used in the rule-based system .

mlSystem ruleFeats + atomFeats We augment mlSystem ruleFeats with more features from our previous work ( Markert et al. , 2012 ; @@CITATIONa ; Hou et al. , 2013b ) on bridging anaphora recognition and antecedent selection .


eagle an extensible architecture for general linguistic engineering”

Breck Baldwin
Christine Doran
Jeffrey Reynar
Michael Niv
Bangalore Srinivas
Mark Wasson

This is similar to `` one sense per collocation '' idea of Yarowsky ( 1993 ) . The description of the EAGLE workbench for linguistic engineering ( Baldwin et al. 1997 ) mentions a case normalization module that uses a heuristic in which a capitalized word in an ambiguous position should be rewritten without capitalization if it is found lower-cased in the same document . This heuristic also employs a database of bigrams and unigrams of lower-cased and capitalized words found in unambiguous positions .

The description of the EAGLE workbench for linguistic engineering ( @@CITATION ) mentions a case normalization module that uses a heuristic in which a capitalized word in an ambiguous position should be rewritten without capitalization if it is found lower-cased in the same document .


coupling niche browsers and affect analysis for an opinion mining application

G Grefenstette
Y Qu
J G Shanahan
D A Evans

There has also been work focused upon determining the political leaning ( e.g. , `` liberal '' vs. `` conservative '' ) of a document or author , where most previously-proposed methods make no direct use of relationships between the documents to be classified ( the `` unlabeled '' texts ) ( Laver et al. , 2003 ; Efron , 2004 ; Mullen and Malouf , 2006 ) . An exception is Grefenstette et al. ( 2004 ) , who experimented with determining the political orientation of websites essentially by classifying the concatenation of all the documents found on that site . Others have applied the NLP technologies of near-duplicate detection and topic-based text categorization to politically oriented text ( Yang and Callan , 2005 ; Purpura and Hillard , 2006 ) .

An exception is @@CITATION , who experimented with determining the political orientation of websites essentially by classifying the concatenation of all the documents found on that site .


Peter F Brown
Stephen A Della Pietra
Vincent J Della Pietra
Meredith J Goldsmith
Jan Hajic
Robert L Mercer
Surya Mohanty

6.1.1 Experiment 1 . Until now , translation models have been evaluated either subjectively ( e.g. White and O'Connell 1993 ) or using relative metrics , such as perplexity with respect to other models ( Brown et al. 1993b ) . Objective and more accurate tests can be carried out using a `` gold standard . ''

Until now , translation models have been evaluated either subjectively ( e.g. White and O'Connell 1993 ) or using relative metrics , such as perplexity with respect to other models ( @@CITATIONb ) .


probabilistic partofspeech tagging using decision trees

Due to the special structure of presentations , this corpus will be particularly demanding with respect to the required preprocessing components of an information retrieval system . The three preprocessing steps ( tokenization , POS-tagging , lemmatization ) are performed using TreeTagger ( Schmid , 1995 ) . The resulting list of POS-tagged lemmas is weighted using the SMART ` ltc ' 8 tf.idf-weighting scheme ( Salton , 1989 ) .

The three preprocessing steps ( tokenization , POS-tagging , lemmatization ) are performed using TreeTagger ( @@CITATION ) .


headdriven statistical models for natural language parsing

Many statistical parsers ( Ratnaparkhi , 1999 ; Collins , 1999 ; Charniak , 2001 ) are based on a history-based probability model ( Black et al. , 1993 ) , where the probability of each decision in a parse is conditioned on the previous decisions in the parse . A major challenge in this approach is choosing a representation of the parse history from which the probability for the next parser decision can be accurately estimated .

Many statistical parsers ( Ratnaparkhi , 1999 ; @@CITATION ; Charniak , 2001 ) are based on a history-based probability model ( Black et al. , 1993 ) , where the probability of each decision in a parse is conditioned on the previous decisions in the parse .


accurate methods for the statistics of surprise and coincidence

For example , Gale and Church ( 1991 , 154 ) suggest that `` 02 , a x2-like statistic , seems to be a particularly good choice because it makes good use of the off-diagonal cells '' in the contingency table . In informal experiments described elsewhere ( Melamed 1995 ) , I found that the G2 statistic suggested by Dunning ( 1993 ) slightly outperforms 02 . Let the cells of the contingency table be named as follows :

In informal experiments described elsewhere ( Melamed 1995 ) , I found that the G2 statistic suggested by @@CITATION slightly outperforms 02 .


efficient probabilistic topdown and leftcorner parsing

These nodes are the left-corner ancestor of top , ( which is below top , on the stack ) , top 's left-corner child ( its leftmost child , if any ) , and top 's most recent child ( which was top , _ 1 , if any ) . For right-branching structures , the leftcorner ancestor is the parent , conditioning on which has been found to be beneficial ( Johnson , 1998 ) , as has conditioning on the left-corner child ( Roark and Johnson , 1999 ) . Because these inputs include the history features of both the leftcorner ancestor and the most recent child , a derivation step i always has access to the history features from the previous derivation step i -- 1 , and thus ( by induction ) any information from the entire previous derivation history could in principle be stored in the history features .

For right-branching structures , the leftcorner ancestor is the parent , conditioning on which has been found to be beneficial ( Johnson , 1998 ) , as has conditioning on the left-corner child ( @@CITATION ) .


This means that the `` it '' that brought the disease in P1 will not be considered to refer to the infection `` i '' or the death `` d '' in P3 . This strategy is certainly the right one to start out with , since anaphora is always the more typical direction of reference in English prose ( Halliday and Hasan 1976 , p. 329 ) . Since techniques developed elsewhere may prove useful , at least for comparison , it is worth mentioning at this point that the proposed metarules are distant cousins of `` unique-name assumption '' ( Genesereth and Nilsson 1987 ) , `` domain closure assumption '' ( ibid . )

This strategy is certainly the right one to start out with , since anaphora is always the more typical direction of reference in English prose ( @@CITATION , p. 329 ) .


restructuring relabeling and realigning for syntaxbased machine translation

Wei Wang
Jonathan May
Kevin Knight
Daniel Marcu

2 ) Parse trees are actually only used to model and explain the monolingual structure , rather than the bilingual mapping between language pairs . This indicates that parse trees are usually not the optimal choice for training tree-based translation models ( Wang et al. , 2010 ) . Based on the above analysis , we can conclude that the tree structure that is independent from Tree-bank resources and simultaneously considers the bilingual mapping inside the bilingual sentence pairs would be a good choice for building treebased translation models .

This indicates that parse trees are usually not the optimal choice for training tree-based translation models ( @@CITATION ) .


The rate of accession may also be represented graphically . In Charniak ( 1996 ) and Krotov et al. ( 1998 ) , it was observed that treebank grammars ( CFGs extracted from treebanks ) are very large and grow with the size of the treebank . We were interested in discovering whether the acquisition of lexical material from the same data displayed a similar propensity .

In @@CITATION and Krotov et al. ( 1998 ) , it was observed that treebank grammars ( CFGs extracted from treebanks ) are very large and grow with the size of the treebank .


an inequality and associated maximization technique in statistical estimation of probabilistic functions of a markov process

Not only do these methods require additional programming outside the toolkit , but they are limited to particular kinds of models and training regimens . For example , the forward-backward algorithm ( Baum , 1972 ) trains only Hidden Markov Models , while ( Ristad and Yianilos , 1996 ) trains only stochastic edit distance . In short , current finite-state toolkits include no training algorithms , because none exist for the large space of statistical models that the toolkits can in principle describe and run .

For example , the forward-backward algorithm ( @@CITATION ) trains only Hidden Markov Models , while ( Ristad and Yianilos , 1996 ) trains only stochastic edit distance .


lilfes — towards a practical hpsg parsers

Takaki Makino
Minoru Yoshida
Kentaro Torisawa
Jun’ichi Tsujii

1In this paper , we use the term LTAG to refer to FBLTAG , if not confusing . ment ( Sarkar and Wintner , 1999 ; Doran et al. , 2000 ; Makino et al. , 1998 ) . These works are restricted to each closed community , and the relation between them is not well discussed .

ment ( Sarkar and Wintner , 1999 ; Doran et al. , 2000 ; @@CITATION ) .


automatic acquisition of a large subcategorisation dictionary from corpora

In addition , subcategorization requirements may vary across linguistic domain or genre ( Carroll and Rooth 1998 ) . Manning ( 1993 ) argues that , aside from missing domain-specific complementation trends , dictionaries produced by hand will tend to lag behind real language use because of their static nature . Given these facts , research on automating acquisition of dictionaries for lexically based NLP systems is a particularly important issue .

@@CITATION argues that , aside from missing domain-specific complementation trends , dictionaries produced by hand will tend to lag behind real language use because of their static nature .


This library has been very popular because it allows researchers to experiment with different methods without having to modify code or reformat data . Finally , the Natural Language Toolkit ( NLTK ) is a package of NLP components implemented in Python ( Loper and Bird , 2002 ) . Python scripting is extremely simple to learn , read and write , and so using the existing components and designing new components is simple .

Finally , the Natural Language Toolkit ( NLTK ) is a package of NLP components implemented in Python ( @@CITATION ) .


language processing technologies for electronic rulemaking a project highlight

Politically-oriented text Sentiment analysis has specifically been proposed as a key enabling technology in eRulemaking , allowing the automatic analysis of the opinions that people submit ( Shulman et al. , 2005 ; Cardie et al. , 2006 ; Kwon et al. , 2006 ) . There has also been work focused upon determining the political leaning ( e.g. , `` liberal '' vs. `` conservative '' ) of a document or author , where most previously-proposed methods make no direct use of relationships between the documents to be classified ( the `` unlabeled '' texts ) ( Laver et al. , 2003 ; Efron , 2004 ; Mullen and Malouf , 2006 ) .

Politically-oriented text Sentiment analysis has specifically been proposed as a key enabling technology in eRulemaking , allowing the automatic analysis of the opinions that people submit ( @@CITATION ; Cardie et al. , 2006 ; Kwon et al. , 2006 ) .


joint parsing and alignment with weakly synchronized grammars

Our U-trees are learned based on STSG , which is more appropriate for tree-based translation models than SCFG . Burkett and Klein ( 2008 ) and Burkett et al. ( 2010 ) focused on joint parsing and alignment . They utilized the bilingual Tree-bank to train a joint model for both parsing and word alignment .

Burkett and Klein ( 2008 ) and @@CITATION focused on joint parsing and alignment .


Developing a calculus for reasoning with QLFs is too large a task to be undertaken here . But the general outlines are reasonably clear , and we can adapt some of the UDRS ( Reyle 1995 ) work to our own framework . Reyle points out that many of the inferences involving underspecified representations that we would like to capture rely on the assumption that whatever context disambiguates the premise also disambiguates the conclusion , even if we do not know what that context or disambiguation is .

But the general outlines are reasonably clear , and we can adapt some of the UDRS ( @@CITATION ) work to our own framework .


parsing indian languages with maltparser

Hence MaltParser features are defined as POS tag at stk [ 0 ] , word-form at buf [ 0 ] , and so on . KUbler , McDonald , and Nivre ( 2009 ) describe a `` typical '' MaltParser model configuration of attributes and features .13 Starting with it , in a series of initial controlled experiments , we settled on using buf [ 0-1 ] + stk [ 0-1 ] for word-forms , and buf [ 0-3 ] + stk [ 0-2 ] for POS tags . For features of new MaltParser-attributes ( discussed later ) , we used buf [ 0 ] + stk [ 0 ] .

KUbler , McDonald , and @@CITATION describe a `` typical '' MaltParser model configuration of attributes and features .13 Starting with it , in a series of initial controlled experiments , we settled on using buf [ 0-1 ] + stk [ 0-1 ] for word-forms , and buf [ 0-3 ] + stk [ 0-2 ] for POS tags .


semantic characteristics of medline citations useful for therapeutic decisionmaking

Charles Sneiderman
Dina Demner-Fushman
Marcelo Fiszman
Thomas C Rindflesch

For some abstracts , MeSH headings can be used as ground truth , because one of the human indexers ' tasks in assigning terms is to identify the main topic of the article ( sometimes a disorder ) . For this evaluation , we randomly selected 50 abstracts with disorders indexed as the main topic from abstracts retrieved using PubMed on the five clinical questions described in Sneiderman et al. ( 2005 ) . We applied our problem extractor on different segments of the abstract : the title only , the title and first two sentences , and the entire abstract .

For this evaluation , we randomly selected 50 abstracts with disorders indexed as the main topic from abstracts retrieved using PubMed on the five clinical questions described in @@CITATION .


can primary care physicians’ questions be answered using the medical journal literature

Paul N Gorman
Joan S Ash
Leslie W Wykoff

For a variety of reasons , medicine is an interesting domain of research . The need for information systems to support physicians at the point of care has been well studied ( Covell et al. , 1985 ; Gorman et al. , 1994 ; Ely et al. , 2005 ) . Retrieval techniques can have a large impact on how physicians access and leverage clinical evidence .

The need for information systems to support physicians at the point of care has been well studied ( Covell et al. , 1985 ; @@CITATION ; Ely et al. , 2005 ) .


parsing strategies in a broadcoverage grammar of english research report rc 12147 ibm tj watson research center

We can also hope for some fine-tuning of the notion of topic , which would prevent many offensive examples . This approach is taken in computational syntactic grammars ( e.g. Jensen 1986 ) ; the number of unlikely parses is severely reduced whenever possible , but no attempt is made to define only the so-called grammatical strings of a language . Finally , as the paragraph is a natural domain in which word senses can be reliably assigned to words or sentences can be syntactically disambiguated , larger chunks of discourse may be needed for precise assignment of topics , which we view as another type of disambiguation .

This approach is taken in computational syntactic grammars ( e.g. @@CITATION ) ; the number of unlikely parses is severely reduced whenever possible , but no attempt is made to define only the so-called grammatical strings of a language .


automatic semantic role labeling for chinese verbs

Compared to the research on English , the research on Chinese SRL is still in its infancy stage . Previous work on Chinese SRL mainly focused on how to transplant the machine learning methods which has been successful with English , such as Sun and Jurafsky ( 2004 ) , Xue and Palmer ( 2005 ) and Xue ( 2008 ) . Sun and Jurafsky ( 2004 ) did the preliminary work on Chinese SRL without any large semantically annotated corpus of Chinese .

Previous work on Chinese SRL mainly focused on how to transplant the machine learning methods which has been successful with English , such as Sun and Jurafsky ( 2004 ) , @@CITATION and Xue ( 2008 ) .


a computational treatment of hpsg lexical rules as covariation in lexical entries

In addition , computationally treating lexical rules on a par with phrase structure rules fails to take computational advantage of their specific properties . For example , the interaction of lexical rules is explored at run-time , even though the possible interaction can be determined at compile-time given the information available in the lexical rules and the base lexical entries .2 Based on the research results reported in Meurers and Minnen ( 1995 , 1996 ) , we propose a new computational treatment of lexical rules that overcomes these shortcomings and results in a more efficient processing of lexical rules as used in HPSG . We developed a compiler that takes as its input a set of lexical rules , deduces the necessary transfer of properties not changed by the individual lexical rules , and encodes the set of lexical rules and their interaction into definite relations constraining lexical entries .

For example , the interaction of lexical rules is explored at run-time , even though the possible interaction can be determined at compile-time given the information available in the lexical rules and the base lexical entries .2 Based on the research results reported in @@CITATION , 1996 ) , we propose a new computational treatment of lexical rules that overcomes these shortcomings and results in a more efficient processing of lexical rules as used in HPSG .


semantic interpretation and the resolution of ambiguity

The idea of using preferences among theories is new , hence it was described in more detail . `` Coherence , '' as outlined above , can be understood as a declarative ( or static ) version of marker passing ( Hirst 1987 ; Charniak 1983 ) , with one difference : the activation spreads to theories that share a predicate , not through the IS-A hierarchy , and is limited to elementary facts about predicates appearing in the text . The metalevel rules we are going to discuss in Section 6 , and that deal with the Gricean maxims and the meaning of `` but , '' can be easily expressed in the languages of set theory or higher order logic , but not everything expressible in those languages makes sense in natural language .

`` Coherence , '' as outlined above , can be understood as a declarative ( or static ) version of marker passing ( @@CITATION ; Charniak 1983 ) , with one difference : the activation spreads to theories that share a predicate , not through the IS-A hierarchy , and is limited to elementary facts about predicates appearing in the text .


a fully bayesian approach to unsupervised partofspeech tagging

As might be expected , our evaluation measures disagree somewhat , but the following broad tendancies seem clear . On small data sets all of the Bayesian estimators strongly outperform EM ( and , to a lesser extent , VB ) with respect to all of our evaluation measures , confirming the results reported in Goldwater and Griffiths ( 2007 ) . This is perhaps not too surprising , as the Bayesian prior plays a comparatively stronger role with a smaller training corpus ( which makes the likelihood term smaller ) and the approximation used by Variational Bayes is likely to be less accurate on smaller data sets .

On small data sets all of the Bayesian estimators strongly outperform EM ( and , to a lesser extent , VB ) with respect to all of our evaluation measures , confirming the results reported in @@CITATION .


the corpusbased study of language change in progress the extra value of tagged corpora

This topic generated intense interest at workshops held at the University of Heidelberg ( October 2004 ) , University of Bologna ( January 2005 ) , University of Birmingham ( July 2005 ) and now in Trento in April 2006 . In addition , the advantages of using linguistically annotated data over raw data are well documented ( Mair , 2005 ; Granger and Rayson , 1998 ) . As the size of a corpus increases , a near linear increase in computing power is required to annotate the text .

In addition , the advantages of using linguistically annotated data over raw data are well documented ( @@CITATION ; Granger and Rayson , 1998 ) .


a formal basis for the heuristic determination of minimum cost pathsquot

10 Some modification of this scheme is necessary when the input stream is not deterministic . For the A * algorithm ( Hart et al. 1968 ) as applied to speech recognition , the actual path score is typically augmented with an estimated score for the unseen portion . Unless some kind of normalization is done , the short theories have an unfair advantage , simply because fewer probability scores have been multiplied .

For the A * algorithm ( @@CITATION ) as applied to speech recognition , the actual path score is typically augmented with an estimated score for the unseen portion .


Figure 4 shows the architecture of Atlas-Andes ; any other system built with APE would look similar . Robust natural language understanding in Atlas-Andes is provided by RosÃ© 's CARMEL system ( RosÃ© 2000 ) ; it uses the spelling correction algorithm devised by Elmi and Evens ( 1998 ) .

Robust natural language understanding in Atlas-Andes is provided by RosÃ© 's CARMEL system ( RosÃ© 2000 ) ; it uses the spelling correction algorithm devised by @@CITATION .


8 History of the Framework and Comparison with Other Systems The framework represents a generalization of several predecessor NLG systems based on Meaning-Text Theory : FoG ( Kittredge and Polguere , 1991 ) , LFS ( Iordanskaja et al. , 1992 ) , and JOYCE ( Rambow and Korelsky , 1992 ) . The framework was originally developed for the realization of deep-syntactic structures in NLG ( Lavoie and Rambow , 1997 ) .

The framework represents a generalization of several predecessor NLG systems based on Meaning-Text Theory : FoG ( Kittredge and Polguere , 1991 ) , LFS ( Iordanskaja et al. , 1992 ) , and JOYCE ( Rambow and @@CITATION ) .


However , marker-normal form grammars can not capture the sorts of regularities demonstrated for languages that do not have a oneto-one mapping between a terminal symbol and a word . Nevertheless , Juola ( 1998 , page 23 ) observes that `` a slightly more general mapping , where two adjacent terminal symbols can be merged into a single lexical item ( for example , a word and its case-marking ) , can capture this sort of result quite handily . '' Work using the marker hypothesis for MT adapts this monolingual mapping for pairs of languages : It is reasonably straightforward to map an English determiner-noun sequence onto a Japanese noun -- case marker segment , once one has identified the sets of marker tags in the languages to be translated .

Nevertheless , @@CITATION , page 23 ) observes that `` a slightly more general mapping , where two adjacent terminal symbols can be merged into a single lexical item ( for example , a word and its case-marking ) , can capture this sort of result quite handily . ''


automated generalization of translation examples

Watanabe ( 1993 ) combines lexical and dependency mappings to form his generalizations . Other similar approaches include those of Cicekli and G Â¨ uvenir ( 1996 ) , McTait and Trujillo ( 1999 ) , Carl ( 1999 ) , and Brown ( 2000 ) , inter alia . In our system , in some cases the smallest chunk obtainable via the marker-based segmentation process may be something like ( 27 ) : ( 27 ) <DET> the good man : le bon homme In such cases , if our system were confronted with a good man , it would not be able to translate such a phrase , assuming this to be missing from the marker lexicon .

Other similar approaches include those of Cicekli and G Â¨ uvenir ( 1996 ) , McTait and Trujillo ( 1999 ) , Carl ( 1999 ) , and @@CITATION , inter alia .


( Och and Ney , 2002 ; Blunsom et al. , 2008 ) used maximum likelihood estimation to learn weights for MT. ( Och , 2003 ; Moore and Quirk , 2008 ; Zhao and Chen , 2009 ; Galley and Quirk , 2011 ) employed an evaluation metric as a loss function and directly optimized it . ( Watanabe et al. , 2007 ; Chiang et al. , 2008 ; Hopkins and May , 2011 ) proposed other optimization objectives by introducing a margin-based and ranking-based indirect loss functions . All the methods mentioned above train a single weight for the whole development set , whereas our local training method learns a weight for each sentence .

( Watanabe et al. , 2007 ; Chiang et al. , 2008 ; @@CITATION ) proposed other optimization objectives by introducing a margin-based and ranking-based indirect loss functions .


transforming trees to improve syntactic convergence

Liu et al. ( 2012 ) re-trained the linguistic parsers bilingually based on word alignment . Burkett and Klein ( 2012 ) utilized a transformation-based method to learn a sequence of monolingual tree transformations for translation . Compared to their work , we do not rely on any Tree-bank resources and focus on generating effective unsupervised tree structures for tree-based translation models .

@@CITATION utilized a transformation-based method to learn a sequence of monolingual tree transformations for translation .


an empirical study of smoothing techniques for language modeling

Our learning framework leaves open a number of design choices : 1 . Baseline language model : For P0 we used a trigram with modified kneser-ney smoothing [ Chen and Goodman , 1998 ] , which is still considered one of the best smoothing methods for n-gram language models . 2 .

Baseline language model : For P0 we used a trigram with modified kneser-ney smoothing [ Chen and @@CITATION ] , which is still considered one of the best smoothing methods for n-gram language models .


headdriven statistical models for natural language parsing

The ACE-2004 dataset is annotated with both mention and mention heads , while the OntoNotes5 .0 dataset only has mention annotations . Therefore , we preprocess Ontonote-5 .0 to derive mention heads using Collins head rules ( Collins , 1999 ) with gold constituency parsing information and gold named entity information . The parsing information9 is only needed to generate training data for the mention head candidate generator and named entities are directly set as heads .

Therefore , we preprocess Ontonote-5 .0 to derive mention heads using Collins head rules ( @@CITATION ) with gold constituency parsing information and gold named entity information .


coarsetofine nbest parsing and maxent discriminative reranking

Second , the diversity of the individual grammars controls the gains that can be obtained by combining multiple grammars into a product model . Our most accurate single grammar achieves an F score of 91.6 on the WSJ test set , rivaling discriminative reranking approaches ( Charniak and Johnson , 2005 ) and products of latent variable grammars ( Petrov , 2010 ) , despite being a single generative PCFG . Our most accurate product model achieves an F score of 92.5 without the use of discriminative reranking and comes close to the best known numbers on this test set ( Zhang et al. , 2009 ) .

Our most accurate single grammar achieves an F score of 91.6 on the WSJ test set , rivaling discriminative reranking approaches ( @@CITATION ) and products of latent variable grammars ( Petrov , 2010 ) , despite being a single generative PCFG .


a simple approach to building ensembles of naive bayesian classifiers for word sense disambiguation

One of our long-term objectives is to identify a core set of features that will be useful for disambiguating a wide class of words using both supervised and unsupervised methodologies . We have presented an ensemble approach to word sense disambiguation ( Pedersen , 2000 ) where multiple Naive Bayesian classifiers , each based on co -- occurrence features from varying sized windows of context , is shown to perform well on the widely studied nouns interest and line . While the accuracy of this approach was as good as any previously published results , the learned models were complex and difficult to interpret , in effect acting as very accurate black boxes .

We have presented an ensemble approach to word sense disambiguation ( @@CITATION ) where multiple Naive Bayesian classifiers , each based on co -- occurrence features from varying sized windows of context , is shown to perform well on the widely studied nouns interest and line .


autotutor a simulation of a human tutor cognitive systems research

A C Graesser
P Wiemer-Hastings
P WiemerHastings
R Kreuz

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 ) . However , most existing systems use pre-authored tutor responses for addressing student errors .

Over the last decade there has been a lot of interest in developing tutorial dialogue systems that understand student explanations ( Jordan et al. , 2006 ; @@CITATION ; 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 ) .


Rather , we stress the possibility that one can axiomatize and productively use such a rule . We shall see this in the next example : two sentences , regarded as a fragment of paragraph , are a variation on a theme by Hobbs ( 1979 ) .

We shall see this in the next example : two sentences , regarded as a fragment of paragraph , are a variation on a theme by @@CITATION .


titpi web people search task using semisupervised clustering approach

Withindocument coreference resolution has been applied to produce summaries of text surrounding occurrences of the name ( Bagga and Baldwin , 1998 ; Gooi and Allan , 2004 ) . 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 ) - . Other representations use the link structure ( Malin , 2005 ) or generate graph representations of the extracted features ( Kalashnikov et al. , 2007 ) .

Nevertheless , the full document text is present in most systems , sometimes as the only feature ( @@CITATION ) and sometimes in combination with others see for instance ( Chen and Martin , 2007 ; Popescu and Magnini , 2007 ) - .


the collection and preliminary analysis of a spontaneous speech databasequot darpa speech and natural language workshop

V Zue
N Daly
J Glass
D Goodine
H Leung
M Phillips
J Polifroni
S Seneff
M Soclof

This aspect of the system is beyond the scope of this paper , and therefore it will not be covered in detail . The recognizer for these systems is the SUMMIT system ( Zue et al. 1989 ) , which uses a segmental-based framework and includes an auditory model in the front-end processing . The lexicon is entered as phonetic pronunciations that are then augmented to account for a number of phonological rules .

The recognizer for these systems is the SUMMIT system ( @@CITATION ) , which uses a segmental-based framework and includes an auditory model in the front-end processing .


textual economy through close coupling of syntax and semantics

Some recent GRE algorithms have done away with the separation between content determination and linguistic realization , interleaving the two processes instead ( Stone and Webber 1998 ; Krahmer and Theune 2002 ) . We have separated the two phases because , in the case of vague descriptions , interleaving would tend to be difficult .

Some recent GRE algorithms have done away with the separation between content determination and linguistic realization , interleaving the two processes instead ( @@CITATION ; Krahmer and Theune 2002 ) .


bayesian inference for pcfgs via markov chain monte carlo

Mark Johnson
Thomas Griffiths
Sharon Goldwater

Our acceptance step is therefore based on the remaining parameters : the context ( Î¸LCTX , Î¸RCTX ) . To sample from our proposal distribution , we use a blocked Gibbs sampler based on the one proposed by Goodman ( 1998 ) and used by Johnson et al. ( 2007 ) that samples entire parse trees . For a sentence w , the strategy is to use the Inside algorithm ( Lari and Young , 1990 ) to inductively compute , for each potential non-terminal position spanning words wi through wj â 1 and category t , going `` up '' the tree , the probability of generating wi , ... , wj â 1 via any arrangement of productions that is rooted by yij = t.

To sample from our proposal distribution , we use a blocked Gibbs sampler based on the one proposed by Goodman ( 1998 ) and used by @@CITATION that samples entire parse trees .


Thus the semantic representations we assume are simply set of literals of the form Pn ( x1 , ... , xn ) where Pn is a predicate of arity n and xi is either a constant or a unification variable whose value will be instantiated during processing . Semantic construction proceeds from the derived tree ( Gardent and Kallmeyer , 2003 ) rather than -- as is more common in TAG -- from the derivation tree . This is done by associating each elementary tree with a semantic representation and by decorating relevant tree nodes with unification variables and constants occuring in associated semantic representation .

Semantic construction proceeds from the derived tree ( @@CITATION ) rather than -- as is more common in TAG -- from the derivation tree .


restricting the weak generative capacity of synchronous tree adjoining grammar

Considering the original definition of S-TAGs , one can see that it does not restrict the structures that can be produced in the source and target languages . It allows the construction of a non-TAL ( Shieber , 1994 ) , ( Harbusch & Poller , 2000 ) . As a result , Shieber ( 1994 ) propose a restricted definition for S-TAG , namely , the IS-TAG for isomorphic S-TAG .

It allows the construction of a non-TAL ( @@CITATION ) , ( Harbusch & Poller , 2000 ) .


a machine learning approach to coreference resolution of noun phrases

Our baseline coreference system uses the C4 .5 decision tree learner ( Quinlan , 1993 ) to acquire a classifier on the training texts for determining whether two NPs are coreferent . Following previous work ( e.g. , Soon et al. ( 2001 ) and Ponzetto and Strube ( 2006 ) ) , we generate training instances as follows : a positive instance is created for each anaphoric NP , NPj , and its closest antecedent , NPi ; and a negative instance is created for NPj paired with each of the intervening NPs , NPi +1 , NPi +2 , ... , NPj_1 . Each instance is represented by 33 lexical , grammatical , semantic , and

Following previous work ( e.g. , @@CITATION and Ponzetto and Strube ( 2006 ) ) , we generate training instances as follows : a positive instance is created for each anaphoric NP , NPj , and its closest antecedent , NPi ; and a negative instance is created for NPj paired with each of the intervening NPs , NPi +1 , NPi +2 , ... , NPj_1 .


In this paper , we use TF-IDF ( a kind of augmented DF ) as a feature selection criterion , in order to ensure results are comparable with those in ( Yahyaoui , 2001 ) . TF-IDF ( term frequency-inverse document frequency ) is one of the widely used feature selection techniques in information retrieval ( Yates and Neto , 1999 ) . Specifically , it is used as a metric for measuring the importance of a word in a document within a collection , so as to improve the recall and the precision of the retrieved documents .

TF-IDF ( term frequency-inverse document frequency ) is one of the widely used feature selection techniques in information retrieval ( @@CITATION ) .


transition network grammars for natural language analysisquot

( Chomsky 1977 ) . The gap mechanism resembles the Hold register idea of ATNs ( Woods 1970 ) and the treatment of bounded domination metavariables in lexical functional grammars ( LFGs ) ( Bresnan 1982 , p. 235 ff . ) , but it is different from these in that the process of filling the Hold register equivalent involves two steps separately initiated by two independent nodes .

The gap mechanism resembles the Hold register idea of ATNs ( @@CITATION ) and the treatment of bounded domination metavariables in lexical functional grammars ( LFGs ) ( Bresnan 1982 , p. 235 ff . )


stochastic variational inference arxiv eprints

Matthew Hoffman
David M Blei
Chong Wang
John Paisley

Prior work using mLDA has used Gibbs Sampling to approximate the posterior , but we found this method did not scale with larger values of K , especially when applied to the relatively large deWaC corpus . To solve these scaling issues , we implement Online Variational Bayesian Inference ( Hoffman et al. , 2010 ; Hoffman et al. , 2012 ) for our models . In Variational Bayesian Inference ( VBI ) , one approximates the true posterior using simpler distributions with free variables .

To solve these scaling issues , we implement Online Variational Bayesian Inference ( Hoffman et al. , 2010 ; @@CITATION ) for our models .