Improving Implicit Discourse Relation Recognition with Discourse-specific Word Embeddings

Changxing Wu, Xiaodong Shi, Yidong Chen, Jinsong Su, Boli Wang


Abstract
We introduce a simple and effective method to learn discourse-specific word embeddings (DSWE) for implicit discourse relation recognition. Specifically, DSWE is learned by performing connective classification on massive explicit discourse data, and capable of capturing discourse relationships between words. On the PDTB data set, using DSWE as features achieves significant improvements over baselines.
Anthology ID:
P17-2042
Volume:
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
Month:
July
Year:
2017
Address:
Vancouver, Canada
Editors:
Regina Barzilay, Min-Yen Kan
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
269–274
Language:
URL:
https://aclanthology.org/P17-2042
DOI:
10.18653/v1/P17-2042
Bibkey:
Cite (ACL):
Changxing Wu, Xiaodong Shi, Yidong Chen, Jinsong Su, and Boli Wang. 2017. Improving Implicit Discourse Relation Recognition with Discourse-specific Word Embeddings. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 269–274, Vancouver, Canada. Association for Computational Linguistics.
Cite (Informal):
Improving Implicit Discourse Relation Recognition with Discourse-specific Word Embeddings (Wu et al., ACL 2017)
Copy Citation:
PDF:
https://aclanthology.org/P17-2042.pdf