Translating Collocations: The Need for Task-driven Word Associations

Oi Yee Kwong


Abstract
Existing dictionaries may help collocation translation by suggesting associated words in the form of collocations, thesaurus, and example sentences. We propose to enhance them with task-driven word associations, illustrating the need by a few scenarios and outlining a possible approach based on word embedding. An example is given, using pre-trained word embedding, while more extensive investigation with more refined methods and resources is underway.
Anthology ID:
2020.cogalex-1.14
Volume:
Proceedings of the Workshop on the Cognitive Aspects of the Lexicon
Month:
December
Year:
2020
Address:
Online
Editors:
Michael Zock, Emmanuele Chersoni, Alessandro Lenci, Enrico Santus
Venue:
CogALex
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
112–116
Language:
URL:
https://aclanthology.org/2020.cogalex-1.14
DOI:
Bibkey:
Cite (ACL):
Oi Yee Kwong. 2020. Translating Collocations: The Need for Task-driven Word Associations. In Proceedings of the Workshop on the Cognitive Aspects of the Lexicon, pages 112–116, Online. Association for Computational Linguistics.
Cite (Informal):
Translating Collocations: The Need for Task-driven Word Associations (Kwong, CogALex 2020)
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PDF:
https://preview.aclanthology.org/nschneid-patch-5/2020.cogalex-1.14.pdf