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Detecting annotation noise in automatically labelled data.

, and . ACL (1), page 1160-1170. Association for Computational Linguistics, (2017)

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Ordering adverbs by their scaling effect on adjective intensity., , , and . RANLP, page 545-554. RANLP 2015 Organising Committee / ACL, (2015)Comparing methods for deriving intensity scores for adjectives., , and . EACL, page 117-122. The Association for Computer Linguistics, (2014)There's no Data like More Data? Revisiting the Impact of Data Size on a Classification Task., and . LREC, European Language Resources Association, (2010)Detecting annotation noise in automatically labelled data., and . ACL (1), page 1160-1170. Association for Computational Linguistics, (2017)Assessing the benefits of partial automatic pre-labeling for frame-semantic annotation., , and . Linguistic Annotation Workshop, page 19-26. The Association for Computer Linguistics, (2009)Shouting and Screaming: Manner and Noise Verbs in Communication., and . LLC, 16 (1): 77-97 (2001)Beyond sentence-level semantic role labeling: linking argument structures in discourse., , , and . Language Resources and Evaluation, 47 (3): 695-721 (2013)Predicative Adjectives: An Unsupervised Criterion to Extract Subjective Adjectives., , and . HLT-NAACL, page 534-539. The Association for Computational Linguistics, (2013)Detection of Abusive Language: the Problem of Biased Datasets., , and . NAACL-HLT (1), page 602-608. Association for Computational Linguistics, (2019)Separating Actor-View from Speaker-View Opinion Expressions using Linguistic Features., , and . HLT-NAACL, page 778-788. The Association for Computational Linguistics, (2016)