TRAVERSAL at PARSEME Shared Task 2018: Identification of Verbal Multiword Expressions Using a Discriminative Tree-Structured Model

Jakub Waszczuk


Abstract
This paper describes a system submitted to the closed track of the PARSEME shared task (edition 1.1) on automatic identification of verbal multiword expressions (VMWEs). The system represents VMWE identification as a labeling task where one of two labels (MWE or not-MWE) must be predicted for each node in the dependency tree based on local context, including adjacent nodes and their labels. The system relies on multiclass logistic regression to determine the globally optimal labeling of a tree. The system ranked 1st in the general cross-lingual ranking of the closed track systems, according to both official evaluation measures: MWE-based F1 and token-based F1.
Anthology ID:
W18-4931
Volume:
Proceedings of the Joint Workshop on Linguistic Annotation, Multiword Expressions and Constructions (LAW-MWE-CxG-2018)
Month:
August
Year:
2018
Address:
Santa Fe, New Mexico, USA
Venue:
LAW
SIGs:
SIGLEX | SIGANN
Publisher:
Association for Computational Linguistics
Note:
Pages:
275–282
Language:
URL:
https://aclanthology.org/W18-4931
DOI:
Bibkey:
Cite (ACL):
Jakub Waszczuk. 2018. TRAVERSAL at PARSEME Shared Task 2018: Identification of Verbal Multiword Expressions Using a Discriminative Tree-Structured Model. In Proceedings of the Joint Workshop on Linguistic Annotation, Multiword Expressions and Constructions (LAW-MWE-CxG-2018), pages 275–282, Santa Fe, New Mexico, USA. Association for Computational Linguistics.
Cite (Informal):
TRAVERSAL at PARSEME Shared Task 2018: Identification of Verbal Multiword Expressions Using a Discriminative Tree-Structured Model (Waszczuk, LAW 2018)
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PDF:
https://aclanthology.org/W18-4931.pdf