Mokanarangan Thayaparan


2019

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Identifying Supporting Facts for Multi-hop Question Answering with Document Graph Networks
Mokanarangan Thayaparan | Marco Valentino | Viktor Schlegel | André Freitas
Proceedings of the Thirteenth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-13)

Recent advances in reading comprehension have resulted in models that surpass human performance when the answer is contained in a single, continuous passage of text. However, complex Question Answering (QA) typically requires multi-hop reasoning - i.e. the integration of supporting facts from different sources, to infer the correct answer. This paper proposes Document Graph Network (DGN), a message passing architecture for the identification of supporting facts over a graph-structured representation of text. The evaluation on HotpotQA shows that DGN obtains competitive results when compared to a reading comprehension baseline operating on raw text, confirming the relevance of structured representations for supporting multi-hop reasoning.

2018

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Graph Based Semi-Supervised Learning Approach for Tamil POS tagging
Mokanarangan Thayaparan | Surangika Ranathunga | Uthayasanker Thayasivam
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)