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Collecting Weighted Coercions from Crowd-Sourced Lexical Data for Compositional Semantic Analysis

Abstract : Type-theoretic frameworks for compositional semantics are aimed at producing structured meaning representations of natural language utterances.
Using elements of lexical semantics, these frameworks are able to model many complex phenomena related to the polysemy of words and their context-dependent meanings. However, they are just as powerful as the lexical resources they can access. This paper explores ways to create and enrich wide-coverage, weighted lexical resources from crowd-sourced data. Specifically, we investigate how existing rich lexical networks – created and validated by serious games – can be used to infer linguistic coercions along with ranking corresponding to preferences in their interpretations.
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Conference papers
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-01916209
Contributor : Isabelle Gouat <>
Submitted on : Thursday, November 8, 2018 - 12:27:50 PM
Last modification on : Thursday, May 16, 2019 - 8:22:01 PM

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Mathieu Lafourcade, Bruno Mery, Mehdi Mirzapour, Richard Moot, Christian Retoré. Collecting Weighted Coercions from Crowd-Sourced Lexical Data for Compositional Semantic Analysis. isAI: International Symposium on Artificial Intelligence, Nov 2017, Tokyo, Japan. pp.214-230, ⟨10.1007/978-3-319-93794-6_15⟩. ⟨lirmm-01916209⟩

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