Title:
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Class-based word sense induction for dot-type nominals
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Author:
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Romeo, Lauren; Martínez Alonso, Héctor; Bel Rafecas, Núria
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Abstract:
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Comunicació presentada a: 6th International Conference on Generative Approaches to the Lexicon, celebrada a Pisa, Itàlia, del 24 al 25 de setembre del 2013. |
Abstract:
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This paper describes an effort to capture the sense alternation of dot-type nominals using Word Sense Induction (WSI). We propose dot-type nominals generate more semantically consistent groupings when clustered into more than two clusters, accounting for literal, metonymic and underspecified senses. Using a class-based approach, we replace individual lemmas with a placeholder representing the entire dot type, which also compensates for data sparsity. Although the distributional evidence does not motivate an individual cluster for each sense, we discuss how our results empirically support theoretical proposals regarding dot types. |
Abstract:
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This work was funded with the support of the SUR of the DEC of the Generalitat de Catalunya and the European Social Fund, by the European Commission’s 7th Framework Program under grant agreement 238405 (CLARA) and by SKATER TIN2012-38584-C06-05. |
Subject(s):
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-Language Resources Automatic Acquisition -Machine Learning -Complex-type nominals -Generative Lexicon |
Rights:
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© ACL, Creative Commons Attribution 3.0 License
https://creativecommons.org/licenses/by-nc-sa/3.0/
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Document type:
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Conference Object Article - Published version |
Published by:
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ACL (Association for Computational Linguistics)
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