Semantic Web Dog Food

Presented at: The Sixth International Language Resources and Evaluation Conference (LREC2008)

by Tejaswini Deoskar, Mats Rooth

We describe the induction of lexical resources from unannotated corpora that are aligned with treebank grammars, providing a systematic correspondence between features in the lexical resource and a treebank syntactic resource. We first describe a methodology based on parsing technology for augmenting a treebank database with linguistic features. A PCFG containing these features is created from the augmented treebank. We then use a procedure based on the inside-outside algorithm to learn lexical resources aligned with the treebank PCFG from large unannotated corpora. The method has been applied in creating a feature-annotated English treebank based on the Penn Treebank. The unsupervised estimation procedure gives a substantial error reduction (up to 31.6%) on the task of learning the subcategorization preference of novel verbs that are not present in the annotated training sample.

Keywords: Lexicon, lexical database, Parsing Systems, Statistical methods, Linguistics

Resource URI on the dog food server: http://data.semanticweb.org/conference/lrec/2008/papers/798

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