USzeged: Identifying Verbal Multiword Expressions with POS Tagging and Parsing Techniques

Katalin Ilona Simkó, Viktória Kovács, Veronika Vincze


Abstract
The paper describes our system submitted for the Workshop on Multiword Expressions’ shared task on automatic identification of verbal multiword expressions. It uses POS tagging and dependency parsing to identify single- and multi-token verbal MWEs in text. Our system is language independent and competed on nine of the eighteen languages. Our paper describes how our system works and gives its error analysis for the languages it was submitted for.
Anthology ID:
W17-1705
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:
48–53
Language:
URL:
https://www.aclweb.org/anthology/W17-1705
DOI:
10.18653/v1/W17-1705
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PDF:
http://aclanthology.lst.uni-saarland.de/W17-1705.pdf