Detection of Verbal Multi-Word Expressions via Conditional Random Fields with Syntactic Dependency Features and Semantic Re-Ranking

Alfredo Maldonado, Lifeng Han, Erwan Moreau, Ashjan Alsulaimani, Koel Dutta Chowdhury, Carl Vogel, Qun Liu


Abstract
A description of a system for identifying Verbal Multi-Word Expressions (VMWEs) in running text is presented. The system mainly exploits universal syntactic dependency features through a Conditional Random Fields (CRF) sequence model. The system competed in the Closed Track at the PARSEME VMWE Shared Task 2017, ranking 2nd place in most languages on full VMWE-based evaluation and 1st in three languages on token-based evaluation. In addition, this paper presents an option to re-rank the 10 best CRF-predicted sequences via semantic vectors, boosting its scores above other systems in the competition. We also show that all systems in the competition would struggle to beat a simple lookup baseline system and argue for a more purpose-specific evaluation scheme.
Anthology ID:
W17-1715
Volume:
Proceedings of the 13th Workshop on Multiword Expressions (MWE 2017)
Month:
April
Year:
2017
Address:
Valencia, Spain
Venues:
MWE | WS
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
114–120
Language:
URL:
https://aclanthology.org/W17-1715
DOI:
10.18653/v1/W17-1715
Bibkey:
Cite (ACL):
Alfredo Maldonado, Lifeng Han, Erwan Moreau, Ashjan Alsulaimani, Koel Dutta Chowdhury, Carl Vogel, and Qun Liu. 2017. Detection of Verbal Multi-Word Expressions via Conditional Random Fields with Syntactic Dependency Features and Semantic Re-Ranking. In Proceedings of the 13th Workshop on Multiword Expressions (MWE 2017), pages 114–120, Valencia, Spain. Association for Computational Linguistics.
Cite (Informal):
Detection of Verbal Multi-Word Expressions via Conditional Random Fields with Syntactic Dependency Features and Semantic Re-Ranking (Maldonado et al., 2017)
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PDF:
https://aclanthology.org/W17-1715.pdf