Detecting and Exploiting Figurative Language in WordNet Wim Peters Department of Computer Science University of Sheffield.

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Presentation transcript:

Detecting and Exploiting Figurative Language in WordNet Wim Peters Department of Computer Science University of Sheffield

Introduction General claim Analysis of WordNet’s and EuroWordNet’s information can give us more in terms of explicit knowledge structures than is currently available. Two types of knowledge explicit knowledge structures already provided by the thesauri such as synonymy, hypernymy and thematic relations implicit information from (Euro)WordNet’s hierarchical structure and the glosses that are associated with each WordNet synset

Phase 1: The detection of patterns of Figurative Language use Regular Polysemy : word senses that are related in systematic and predictable ways. Systematic sense distributions of nouns in WordNet Characterization of regular polysemic patterns by means of pairs of hypernyms

Regular Polysemy: Profession - Discipline

Phase 2: Extracting relations that exist between the word senses A nalysis of the part of speech tagged and lemmatized glosses Set of synonyms and hypernyms Set of synonyms and hypernyms Gloss synset 1 and 2 Gloss hypernyms synset 1 and 2 “… word 1 … VERB … word 2…” Word sense 1 Word sense 2 match Create bag of words

Example

Hypernymic collocates of ‘Discipline’ Music – Dance: tango, bolero, waltz….. Person-play-Music Composer-make-Music Music-accompany-Activity

Extended knowledge frame for ‘Music’