The CoNLL-2015 shared task on shallow discourse parsing

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Abstract

The CoNLL-2015 Shared Task is on Shallow Discourse Parsing, a task focusing on identifying individual discourse relations that are present in a natural language text. A discourse relation can be expressed explicitly or implicitly, and takes two arguments realized as sentences, clauses, or in some rare cases, phrases. Sixteen teams from three continents participated in this task. For the first time in the history of the CoNLL shared tasks, participating teams, instead of running their systems on the test set and submitting the output, were asked to deploy their systems on a remote virtual machine and use a web-based evaluation platform to run their systems on the test set. This meant they were unable to actually see the data set, thus preserving its integrity and ensuring its replicability. In this paper, we present the task definition, the training and test sets, and the evaluation protocol and metric used during this shared task. We also summarize the different approaches adopted by the participating teams, and present the evaluation results. The evaluation data sets and the scorer will serve as a benchmark for future research on shallow discourse parsing.

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APA

Xue, N., Ng, H. T., Pradhan, S., Prasad, R., Bryant, C., & Rutherford, A. T. (2014). The CoNLL-2015 shared task on shallow discourse parsing. In CoNLL 2015 - 19th Conference on Computational Natural Language Learning, Proceedings of the Shared Task (pp. 1–16). Curran Associates Inc. https://doi.org/10.18653/v1/k15-2001

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