A Flexible and Easy-to-use Semantic Role Labeling Framework for Different Languages

Quynh Ngoc Thi Do, Artuur Leeuwenberg, Geert Heyman, Marie-Francine Moens


Abstract
This paper presents a flexible and open source framework for deep semantic role labeling. We aim at facilitating easy exploration of model structures for multiple languages with different characteristics. It provides flexibility in its model construction in terms of word representation, sequence representation, output modeling, and inference styles and comes with clear output visualization. The framework is available under the Apache 2.0 license.
Anthology ID:
C18-2035
Volume:
Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations
Month:
August
Year:
2018
Address:
Santa Fe, New Mexico
Venue:
COLING
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
161–165
Language:
URL:
https://www.aclweb.org/anthology/C18-2035
DOI:
Bib Export formats:
BibTeX MODS XML EndNote
PDF:
http://aclanthology.lst.uni-saarland.de/C18-2035.pdf