tailieunhanh - Báo cáo khoa học: "A Logic-based Semantic Approach to Recognizing Textual Entailment"

This paper proposes a knowledge representation model and a logic proving setting with axioms on demand successfully used for recognizing textual entailments. It also details a lexical inference system which boosts the performance of the deep semantic oriented approach on the RTE data. The linear combination of two slightly different logical systems with the third lexical inference system achieves accuracy on the RTE 2006 data. | A Logic-based Semantic Approach to Recognizing Textual Entailment Marta Tatu and Dan Moldovan Language Computer Corporation Richardson Texas 75080 United States of America marta moldovan@ Abstract This paper proposes a knowledge representation model and a logic proving setting with axioms on demand successfully used for recognizing textual entailments. It also details a lexical inference system which boosts the performance of the deep semantic oriented approach on the RTE data. The linear combination of two slightly different logical systems with the third lexical inference system achieves accuracy on the RTE 2006 data. 1 Introduction While communicating humans use different expressions to convey the same meaning. One of the central challenges for natural language understanding systems is to determine whether different text fragments have the same meaning or more generally if the meaning of one text can be derived from the meaning of another. A module that recognizes the semantic entailment between two text snippets can be employed by many NLP applications. For example Question Answering systems have to identify texts that entail expected answers. In Multi-document Summarization the redundant information should be recognized and omitted from the summary. Trying to boost research in textual inferences the PASCAL Network proposed the Recognizing Textual Entailment rte challenges Dagan et al. 2005 Bar-Haim et al. 2006 . For a pair of two text fragments the task is to determine if the meaning of one text the entailed hypothesis denoted by H can be inferred from the meaning of the other text the entailing text or 7 In this paper we propose a model to represent the knowledge encoded in text and a logical setting suitable to a recognizing semantic entailment system. We cast the textual inference problem as a logic implication between meanings. Text T semantically entails if its meaning logically implies the meaning of H. Thus we first transform .