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2018 | OriginalPaper | Buchkapitel

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

verfasst von : Mathieu Lafourcade, Bruno Mery, Mehdi Mirzapour, Richard Moot, Christian Retoré

Erschienen in: New Frontiers in Artificial Intelligence

Verlag: Springer International Publishing

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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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Vorheriges Kapitel Pictorial and Alphabet Writings in Asymmetric Signaling Games

Nächstes Kapitel How Dogwhistles Work

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Titel: Collecting Weighted Coercions from Crowd-Sourced Lexical Data for Compositional Semantic Analysis
verfasst von: Mathieu Lafourcade
Bruno Mery
Mehdi Mirzapour
Richard Moot
Christian Retoré
Verlag: Springer International Publishing
Buch: New Frontiers in Artificial Intelligence
Print ISBN: 978-3-319-93793-9

Electronic ISBN: 978-3-319-93794-6

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-93794-6_15

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