Recognizing Textual Entailment with LCC's GROUNDHOG System

msra(2005)

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摘要
We introduce a new system for rec- ognizing textual entailment (known as GROUNDHOG) which utilizes a classification-based approach to combine lexico-semantic information derived from text processing applications with a large collection of paraphrases acquired automatically from the WWW. Trained on 200,000 examples of textual entailment extracted from newswire corpora, our system managed to classify more than 75% of the pairs in the 2006 PASCAL RTE Test Set correctly.
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