Abstract
The task of morphological analysis is to produce a complete list of lemma+tag analyses for a given word-form. We propose a discriminative string transduction approach which exploits plain inflection tables and raw text corpora, thus obviating the need for expert annotation. Experiments on four languages demonstrate that our system has much higher coverage than a hand-engineered FST analyzer, and is more accurate than a state-of-the-art morphological tagger.- Anthology ID:
- E17-2034
- Volume:
- Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers
- Month:
- April
- Year:
- 2017
- Address:
- Valencia, Spain
- Editors:
- Mirella Lapata, Phil Blunsom, Alexander Koller
- Venue:
- EACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 211–216
- Language:
- URL:
- https://aclanthology.org/E17-2034
- DOI:
- Cite (ACL):
- Garrett Nicolai and Grzegorz Kondrak. 2017. Morphological Analysis without Expert Annotation. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, pages 211–216, Valencia, Spain. Association for Computational Linguistics.
- Cite (Informal):
- Morphological Analysis without Expert Annotation (Nicolai & Kondrak, EACL 2017)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/E17-2034.pdf
- Data
- CELEX