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 12th Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Venues:
COLING | LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
5202–5207
Language:
English
URL:
https://www.aclweb.org/anthology/2020.lrec-1.640
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.lrec-1.640.pdf