Inferences for Lexical Semantic Resource Building with Less Supervision

Nadia Bebeshina, Mathieu Lafourcade


Abstract
Lexical semantic resources may be built using various approaches such as extraction from corpora, integration of the relevant pieces of knowledge from the pre-existing knowledge resources, and endogenous inference. Each of these techniques needs human supervision in order to deal with the potential errors, mapping difficulties or inferred candidate validation. We detail how various inference processes can be employed for the less supervised lexical semantic resource building. Our experience is based on the combination of different inference techniques for multilingual resource building and evaluation.
Anthology ID:
2020.lrec-1.280
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
2300–2305
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.280
DOI:
Bibkey:
Cite (ACL):
Nadia Bebeshina and Mathieu Lafourcade. 2020. Inferences for Lexical Semantic Resource Building with Less Supervision. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 2300–2305, Marseille, France. European Language Resources Association.
Cite (Informal):
Inferences for Lexical Semantic Resource Building with Less Supervision (Bebeshina & Lafourcade, LREC 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.lrec-1.280.pdf