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A Benchmark Dataset for Automatic Detection of Claims and Evidence in the Context of Controversial Topics.

, , , , , , , and . ArgMining@ACL, page 64-68. The Association for Computer Linguistics, (2014)

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Towards Effective Rebuttal: Listening Comprehension Using Corpus-Wide Claim Mining., , , , , , , , , and . ArgMining@ACL, page 58-66. Association for Computational Linguistics, (2019)A Benchmark Dataset for Automatic Detection of Claims and Evidence in the Context of Controversial Topics., , , , , , , and . ArgMining@ACL, page 64-68. The Association for Computer Linguistics, (2014)Listening Comprehension over Argumentative Content., , , , , , , , , and . EMNLP, page 719-724. Association for Computational Linguistics, (2018)A Recorded Debating Dataset., , , , , , , , and . CoRR, (2017)Integrating Copies Obtained from Old and New Preservation Efforts., , , and . ICDAR, page 47-51. IEEE Computer Society, (2013)Supporting Spanish Writers using Automated Feedback., , , , , , , and . NAACL-HLT (Demonstrations), page 116-124. Association for Computational Linguistics, (2021)Claims on demand - an initial demonstration of a system for automatic detection and polarity identification of context dependent claims in massive corpora., , , , , , , , , and 10 other author(s). COLING (Demos), page 6-9. ACL, (2014)A Recorded Debating Dataset., , , , , , , , and . LREC, European Language Resources Association (ELRA), (2018)A Dataset of General-Purpose Rebuttal., , , , , , , , , and 1 other author(s). EMNLP/IJCNLP (1), page 5590-5600. Association for Computational Linguistics, (2019)