Abstract
In this paper we describe our work on the development and enrichment of OFrLex, a freely available, large-coverage morphological and syntactic Old French lexicon. We rely on several heterogeneous language resources to extract structured and exploitable information. The extraction follows a semi-automatic procedure with substantial manual steps to respond to difficulties encountered while aligning lexical entries from distinct language resources. OFrLex aims at improving natural language processing tasks on Old French such as part-of-speech tagging and dependency parsing. We provide quantitative information on OFrLex and discuss its reliability. We also describe and evaluate a semi-automatic, word-embedding-based lexical enrichment process aimed at increasing the accuracy of the resource. Results of this extension technique will be manually validated in the near future, a step that will take advantage of OFrLex’s viewing, searching and editing interface, which is already accessible online.- Anthology ID:
- 2020.lrec-1.393
- 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:
- 3217–3225
- Language:
- English
- URL:
- https://aclanthology.org/2020.lrec-1.393
- DOI:
- Cite (ACL):
- Gaël Guibon and Benoît Sagot. 2020. OFrLex: A Computational Morphological and Syntactic Lexicon for Old French. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 3217–3225, Marseille, France. European Language Resources Association.
- Cite (Informal):
- OFrLex: A Computational Morphological and Syntactic Lexicon for Old French (Guibon & Sagot, LREC 2020)
- PDF:
- https://preview.aclanthology.org/emnlp22-frontmatter/2020.lrec-1.393.pdf