Integrating Pattern-Based and Distributional Similarity Methods for Lexical Entailment Acquisition

This paper addresses the problem of acquiring lexical semantic relationships, applied to the lexical entailment relation. Our main contribution is a novel conceptual integration between the two distinct acquisition paradigms for lexical relations - the pattern-based and the distributional similarity approaches. The integrated method exploits mutual complementary information of the two approaches to obtain candidate relations and informative characterizing features. Then, a small size training set is used to construct a more accurate supervised classifier, showing significant increase in both recall and precision over the original approaches.

• Publication year

  2006

• Venue

  Annual Meeting of the Association for Computational Linguistics

• Publication date

  2006-07-17

• Fields of study

  Linguistics, Computer Science

• Identifiers
  DOI 10.3115/1273073.1273148
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• PhD dissertation

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