Cross-Lingual Transfer of Semantic Roles: From Raw Text to Semantic Roles

Maryam Aminian, Mohammad Sadegh Rasooli, Mona Diab


Abstract
We describe a transfer method based on annotation projection to develop a dependency-based semantic role labeling system for languages for which no supervised linguistic information other than parallel data is available. Unlike previous work that presumes the availability of supervised features such as lemmas, part-of-speech tags, and dependency parse trees, we only make use of word and character features. Our deep model considers using character-based representations as well as unsupervised stem embeddings to alleviate the need for supervised features. Our experiments outperform a state-of-the-art method that uses supervised lexico-syntactic features on 6 out of 7 languages in the Universal Proposition Bank.
Anthology ID:
W19-0417
Volume:
Proceedings of the 13th International Conference on Computational Semantics - Long Papers
Month:
May
Year:
2019
Address:
Gothenburg, Sweden
Venues:
IWCS | WS
SIG:
SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
200–210
Language:
URL:
https://www.aclweb.org/anthology/W19-0417
DOI:
10.18653/v1/W19-0417
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PDF:
http://aclanthology.lst.uni-saarland.de/W19-0417.pdf