This paper describes our submission (kosseim15) to the CoNLL-2015 shared task on shallow discourse parsing. We used the UIMA framework to develop our parser and used ClearTK to add machine learning functionality to the UIMA framework. Overall, our parser achieves a result of 17.3 F1 on the identification of discourse relations on the blind CoNLL-2015 test set, ranking in sixth place.
Cite
@article{arxiv.1708.05857,
title = {The CLaC Discourse Parser at CoNLL-2015},
author = {Majid Laali and Elnaz Davoodi and Leila Kosseim},
journal= {arXiv preprint arXiv:1708.05857},
year = {2017}
}
Comments
Proceedings of the Nineteenth Conference on Computational Natural Language Learning Shared Task (CoNLL 2015). Beijing, China