Paper: The Distributional Inclusion Hypotheses And Lexical Entailment

ACL ID P05-1014
Title The Distributional Inclusion Hypotheses And Lexical Entailment
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2005
Authors

This paper suggests refinements for the Distributional Similarity Hypothesis. Our proposed hypotheses relate the distribu- tional behavior of pairs of words to lexical entailment – a tighter notion of semantic similarity that is required by many NLP applications. To automatically explore the validity of the defined hypotheses we de- veloped an inclusion testing algorithm for characteristic features of two words, which incorporates corpus and web-based feature sampling to overcome data sparseness. The degree of hypotheses validity was then em- pirically tested and manually analyzed with respect to the word sense level. In addition, the above testing algorithm was exploited to improve lexical entailment acquisition.