Learning Event Expressions via Bilingual Structure Projection

Fangyuan Li, Ruihong Huang, Deyi Xiong, Min Zhang


Abstract
Identifying events of a specific type is a challenging task as events in texts are described in numerous and diverse ways. Aiming to resolve high complexities of event descriptions, previous work (Huang and Riloff, 2013) proposes multi-faceted event recognition and a bootstrapping method to automatically acquire both event facet phrases and event expressions from unannotated texts. However, to ensure high quality of learned phrases, this method is constrained to only learn phrases that match certain syntactic structures. In this paper, we propose a bilingual structure projection algorithm that explores linguistic divergences between two languages (Chinese and English) and mines new phrases with new syntactic structures, which have been ignored in the previous work. Experiments show that our approach can successfully find novel event phrases and structures, e.g., phrases headed by nouns. Furthermore, the newly mined phrases are capable of recognizing additional event descriptions and increasing the recall of event recognition.
Anthology ID:
C16-1136
Volume:
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
Month:
December
Year:
2016
Address:
Osaka, Japan
Editors:
Yuji Matsumoto, Rashmi Prasad
Venue:
COLING
SIG:
Publisher:
The COLING 2016 Organizing Committee
Note:
Pages:
1441–1450
Language:
URL:
https://aclanthology.org/C16-1136
DOI:
Bibkey:
Cite (ACL):
Fangyuan Li, Ruihong Huang, Deyi Xiong, and Min Zhang. 2016. Learning Event Expressions via Bilingual Structure Projection. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 1441–1450, Osaka, Japan. The COLING 2016 Organizing Committee.
Cite (Informal):
Learning Event Expressions via Bilingual Structure Projection (Li et al., COLING 2016)
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PDF:
https://preview.aclanthology.org/nschneid-patch-4/C16-1136.pdf