CLAug 19, 2017
The CLaC Discourse Parser at CoNLL-2015
arXiv:1708.05857v11088 citations
Originality Synthesis-oriented
AI Analysis
This is an incremental contribution to discourse parsing for NLP researchers, with a specific benchmark performance.
The paper tackled shallow discourse parsing in the CoNLL-2015 shared task, achieving a result of 17.3 F1 on discourse relation identification, ranking sixth.
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.