Abstract
This paper adds to the available resources for the under-resourced language Urdu by converting different types of existing treebanks for Urdu into a common format that is based on Universal Dependencies. We present comparative results for training two dependency parsers, the MaltParser and a transition-based BiLSTM parser on this new resource. The BiLSTM parser incorporates word embeddings which improve the parsing results significantly. The BiLSTM parser outperforms the MaltParser with a UAS of 89.6 and an LAS of 84.2 with respect to our standardized treebank resource.- Anthology ID:
- 2020.lrec-1.640
- 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:
- 5202–5207
- Language:
- English
- URL:
- https://aclanthology.org/2020.lrec-1.640
- DOI:
- Cite (ACL):
- Toqeer Ehsan and Miriam Butt. 2020. Dependency Parsing for Urdu: Resources, Conversions and Learning. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 5202–5207, Marseille, France. European Language Resources Association.
- Cite (Informal):
- Dependency Parsing for Urdu: Resources, Conversions and Learning (Ehsan & Butt, LREC 2020)
- PDF:
- https://preview.aclanthology.org/naacl24-info/2020.lrec-1.640.pdf