Paper: A Semantic Approach To Recognizing Textual Entailment

ACL ID H05-1047
Title A Semantic Approach To Recognizing Textual Entailment
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2005

Exhaustive extraction of semantic infor- mation from text is one of the formidable goals of state-of-the-art NLP systems. In this paper, we take a step closer to this objective. We combine the semantic in- formation provided by different resources and extract new semantic knowledge to improve the performance of a recognizing textual entailment system. 1 Recognizing Textual Entailment While communicating, humans use different expres- sions to convey the same meaning. Therefore, nu- merous NLP applications, such as, Question An- swering, Information Extraction, or Summarization require computational models of language that rec- ognize if two texts semantically overlap. Trying to capture the major inferences needed to understand equivalent semantic expressions, the PASCAL Net- work proposed t...