CEA LIST: Processing Low-Resource Languages for CoNLL 2018

Elie Duthoo, Olivier Mesnard


Abstract
In this paper, we describe the system used for our first participation at the CoNLL 2018 shared task. The submitted system largely reused the state of the art parser from CoNLL 2017 (https://github.com/tdozat/Parser-v2). We enhanced this system for morphological features predictions, and we used all available resources to provide accurate models for low-resource languages. We ranked 5th of 27 participants in MLAS for building morphology aware dependency trees, 2nd for morphological features only, and 3rd for tagging (UPOS) and parsing (LAS) low-resource languages.
Anthology ID:
K18-2003
Volume:
Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
Month:
October
Year:
2018
Address:
Brussels, Belgium
Editors:
Daniel Zeman, Jan Hajič
Venue:
CoNLL
SIG:
SIGNLL
Publisher:
Association for Computational Linguistics
Note:
Pages:
34–44
Language:
URL:
https://aclanthology.org/K18-2003
DOI:
10.18653/v1/K18-2003
Bibkey:
Cite (ACL):
Elie Duthoo and Olivier Mesnard. 2018. CEA LIST: Processing Low-Resource Languages for CoNLL 2018. In Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, pages 34–44, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):
CEA LIST: Processing Low-Resource Languages for CoNLL 2018 (Duthoo & Mesnard, CoNLL 2018)
Copy Citation:
PDF:
https://aclanthology.org/K18-2003.pdf
Code
 tdozat/Parser-v2