Abstract
We investigate the manual and automatic annotation of PDTB discourse relations in student essays, a novel domain that is not only learning-based and argumentative, but also noisy with surface errors and deeper coherency issues. We discuss methodological complexities it poses for the task. We present descriptive statistics and compare relation distributions in related corpora. We compare automatic discourse parsing performance to prior work.
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CITATION STYLE
Forbes-Riley, K., Zhang, F., & Litman, D. (2016). Extracting PDTB Discourse Relations from Student Essays. In SIGDIAL 2016 - 17th Annual Meeting of the Special Interest Group on Discourse and Dialogue, Proceedings of the Conference (pp. 117–127). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w16-3615
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