A shallow discourse parsing system based on maximum entropy model

1Citations
Citations of this article
60Readers
Mendeley users who have this article in their library.

Abstract

This paper describes our system for Shallow Discourse Parsing - the CoNLL 2015 Shared Task. We regard this as a classification task and build a cascaded system based on Maximum Entropy to identify the discourse connective, the spans of two arguments and the sense of the discourse connective. We trained the cascaded models with a variety of features such as lexical and syntactic features. We also report the results achieved by our team.

Cite

CITATION STYLE

APA

Sun, J., Li, P., Xu, W., & Yan, Y. (2014). A shallow discourse parsing system based on maximum entropy model. In CoNLL 2015 - 19th Conference on Computational Natural Language Learning, Proceedings of the Shared Task (pp. 84–88). Curran Associates Inc. https://doi.org/10.18653/v1/k15-2013

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free