TermEval 2020: TALN-LS2N System for Automatic Term Extraction

Amir Hazem, Mérieme Bouhandi, Florian Boudin, Beatrice Daille


Abstract
Automatic terminology extraction is a notoriously difficult task aiming to ease effort demanded to manually identify terms in domain-specific corpora by automatically providing a ranked list of candidate terms. The main ways that addressed this task can be ranged in four main categories: (i) rule-based approaches, (ii) feature-based approaches, (iii) context-based approaches, and (iv) hybrid approaches. For this first TermEval shared task, we explore a feature-based approach, and a deep neural network multitask approach -BERT- that we fine-tune for term extraction. We show that BERT models (RoBERTa for English and CamemBERT for French) outperform other systems for French and English languages.
Anthology ID:
2020.computerm-1.13
Volume:
Proceedings of the 6th International Workshop on Computational Terminology
Month:
May
Year:
2020
Address:
Marseille, France
Venues:
CompuTerm | LREC | WS
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
95–100
Language:
English
URL:
https://www.aclweb.org/anthology/2020.computerm-1.13
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.computerm-1.13.pdf