Neural Disambiguation of Lemma and Part of Speech in Morphologically Rich Languages
José María Hoya Quecedo, Koppatz Maximilian, Roman Yangarber
Abstract
We consider the problem of disambiguating the lemma and part of speech of ambiguous words in morphologically rich languages. We propose a method for disambiguating ambiguous words in context, using a large un-annotated corpus of text, and a morphological analyser—with no manual disambiguation or data annotation. We assume that the morphological analyser produces multiple analyses for ambiguous words. The idea is to train recurrent neural networks on the output that the morphological analyser produces for unambiguous words. We present performance on POS and lemma disambiguation that reaches or surpasses the state of the art—including supervised models—using no manually annotated data. We evaluate the method on several morphologically rich languages.- Anthology ID:
- 2020.lrec-1.439
- 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:
- 3573–3582
- Language:
- English
- URL:
- https://aclanthology.org/2020.lrec-1.439
- DOI:
- Cite (ACL):
- José María Hoya Quecedo, Koppatz Maximilian, and Roman Yangarber. 2020. Neural Disambiguation of Lemma and Part of Speech in Morphologically Rich Languages. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 3573–3582, Marseille, France. European Language Resources Association.
- Cite (Informal):
- Neural Disambiguation of Lemma and Part of Speech in Morphologically Rich Languages (Hoya Quecedo et al., LREC 2020)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2020.lrec-1.439.pdf