Shallow discourse parsing enables us to study discourse as a coherent piece of information rather than a sequence of clauses, sentences and paragraphs. In this paper, we identify arguments of explicit discourse relations in Hindi. This is the first such work carried out for Hindi. Building upon previous work carried out on discourse connective identification in Hindi, we propose a hybrid pipeline which makes use of both sub-tree extraction and linear tagging approaches. We report state-ofthe- art performance for this task.
CITATION STYLE
Jain, R., & Sharma, D. M. (2016). Explicit argument identification for discourse parsing in hindi: A hybrid pipeline. In HLT-NAACL 2016 - 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Student Research Workshop (pp. 66–72). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/n16-2010
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