Discourse parsing is a challenging task and is crucial for discourse analysis. In this paper, we focus on labelling argument spans of discourse connectives and sense identification in the CoNLL-2015 shared task setting. We have used syntactic features and have also tried a few semantic features. We employ a pipeline of classifiers, where the best features and parameters were selected for each individual classifier, based on experimental evaluation. We could only get results somewhat better than of the baseline on the overall task, but the results over some of the sub-tasks are encouraging. Our initial efforts at using semantic features do not seem to help.
CITATION STYLE
Mukherjee, S., Tiwari, A., Gupta, M., & Singh, A. K. (2014). Shallow discourse parsing with syntactic and (a few) semantic features. In CoNLL 2015 - 19th Conference on Computational Natural Language Learning, Proceedings of the Shared Task (pp. 61–65). Curran Associates Inc. https://doi.org/10.18653/v1/k15-2009
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