Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Counts from large corpora (like the b) can be porful syntactic cues. Past work has used b counts to help resolve isolated ambiguities, such as binary noun-verb PP attachments and noun compound bracketings. In this work,  first present a method for generating b count features that address the full range of syntactic attachments. These features encode both surface evidence of lexical affinities as ll as paraphrase-based cues to syntactic structure.  then integrate our features into full-scale dependency and constituent parsers.  show relative error reductions of 7.0% over the second-order dependency parser of McDonald and Pereira (2006), 9.2% over the constituent parser of Petrov et al. (2006), and 3.4% over a non-local constituent reranker.
['Mohit Bansal', 'Daniel N. Klein']
I am writing a research paper on a idea Web-Scale Features for Full-Scale Parsing
[{"from": "human", "value": "I am writing a research paper on a idea Web-Scale Features for Full-Scale Parsing"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Counts from large corpora (like the b) can be porful syntactic cues. Past work has used b counts to help resolve isolated ambiguities, such as binary noun-verb PP attachments and noun compound bracketings. In this work,  first present a method for generating b count features that address the full range of syntactic attachments. These features encode both surface evidence of lexical affinities as ll as paraphrase-based cues to syntactic structure.  then integrate our features into full-scale dependency and constituent parsers.  show relative error reductions of 7.0% over the second-order dependency parser of McDonald and Pereira (2006), 9.2% over the constituent parser of Petrov et al. (2006), and 3.4% over a non-local constituent reranker."}]