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Learning to distinguish hypernyms and co-hyponyms

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conference contribution
posted on 2023-06-08, 20:09 authored by Julie WeedsJulie Weeds, Daoud Clarke, Jeremy ReffinJeremy Reffin, David WeirDavid Weir, Bill Keller
This work is concerned with distinguishing different semantic relations which exist between distributionally similar words. We compare a novel approach based on training a linear Support Vector Machine on pairs of feature vectors with state-of-the-art methods based on distributional similarity. We show that the new supervised approach does better even when there is minimal information about the target words in the training data, giving a 15% reduction in error rate over unsupervised approaches.

History

Publication status

  • Published

File Version

  • Published version

Journal

Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers

Publisher

Dublin City University and Association for Computational Linguistics

Volume

0

Page range

2249-2259

Event name

COLING 2014, the 25th International Conference on Computational Linguistics

Event location

Dublin, Ireland

Event type

conference

Event date

August 23-29 2014

Place of publication

Dublin, Ireland

Department affiliated with

  • Informatics Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2015-02-27

First Open Access (FOA) Date

2015-02-27

First Compliant Deposit (FCD) Date

2015-02-27

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