Dependency Parsing for Urdu: Resources, Conversions and Learning

Toqeer Ehsan, Miriam Butt


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:
Bibkey:
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)
Copy Citation:
PDF:
https://aclanthology.org/2020.lrec-1.640.pdf