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1
SemEval 2021 Task 12: Learning with Disagreement ...
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2
SemEval-2021 Task 12: Learning with Disagreements
Uma, Alexandra; Fornaciari, Tommaso; Dumitrache, Anca. - : Association for Computational Linguistics, 2021
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3
Phrase Detectives Corpus Version 2
Chamberlain, Jon; Paun, Silviu; Yu, Juntao. - : Linguistic Data Consortium, 2019. : https://www.ldc.upenn.edu, 2019
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4
Phrase Detectives Corpus Version 2 ...
Chamberlain, Jon; Paun, Silviu; Yu, Juntao. - : Linguistic Data Consortium, 2019
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5
Crowdsourcing and Aggregating Nested Markable Annotations ...
Madge, Chris; Yu, Juntao; Chamberlain, Jon. - : Universität Regensburg, 2019
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6
Crowdsourcing and Aggregating Nested Markable Annotations
Madge, Chris; Yu, Juntao; Chamberlain, Jon. - : Association for Computational Linguistics, 2019
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7
A Crowdsourced Corpus of Multiple Judgments and Disagreement on Anaphoric Interpretation
Paun, Silviu; Uma, Alexandra; Poesio, Massimo. - : Association for Computational Linguistics, 2019
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8
Crowdsourcing and Aggregating Nested Markable Annotations
Poesio, Massimo; Yu, Juntao; Chamberlain, Jon. - : Association for Computational Linguistics, 2019
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9
A Crowdsourced Corpus of Multiple Judgments and Disagreement on Anaphoric Interpretation
Poesio, Massimo; Chamberlain, Jon; Paun, Silviu. - : Association for Computational Linguistics, 2019
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10
Exploring Language Style in Chatbots to Increase Perceived Product Value and User Engagement
Elsholz, Ela; Chamberlain, Jon; Kruschwitz, Udo. - : ACM (Association for Computing Machinery), 2019
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11
A Probabilistic Annotation Model for Crowdsourcing Coreference
Kruschwitz, Udo; Chamberlain, Jon; Yu, Juntao. - : Association for Computational Linguistics, 2018
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12
Phrase Detectives Corpus
Chamberlain, Jon; Poesio, Massimo; Kruschwitz, Udo. - : Linguistic Data Consortium, 2017. : https://www.ldc.upenn.edu, 2017
Abstract: *Introduction* Phrase Detectives Corpus was developed by the School of Computer Science and Electronic Engineering at the University of Essex and consists of approximately 19,012 words across 40 documents anaphorically-annotated by the Phrase Detectives game, an online interactive "game-with-a-purpose" (GWAP) designed to collect data about English anaphoric coreference. GWAPs for creating language resources are growing. In general, they employ non-monetary incentives, such as entertainment, to motivate participation and can be successful for large-scale persistent annotation efforts. *Data* The documents in the corpus are taken from Wikipedia articles and from narrative text in Project Gutenberg. Wikipedia articles and annotation files are presented as XML and Project Gutenberg source files are presented as plain text. All text is encoded as UTF-8. Annotations are comprised of a gold standard version created by multiple experts, as well as a set created by a large non-expert crowd (via the Phase Detectives game). The data was annotated according to a prevalent linguistically-oriented approach for anaphora used in several tasks, including OntoNotes Release 5.0 (LDC2013T19), SemEval-2010 Task 1 Ontonotes English: Coreference Resolution in Multiple Languages (LDC2011T01) and The ARRAU Corpus of Anaphoric Information (LDC2013T22). *Samples* Please view the following source sample and annotation sample. *Updates* None at this time.
URL: https://catalog.ldc.upenn.edu/LDC2017T08
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13
Phrase Detectives Corpus ...
Chamberlain, Jon; Poesio, Massimo; Kruschwitz, Udo. - : Linguistic Data Consortium, 2017
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14
Markup Infrastructure for the Anaphoric Bank: Supporting Web Collaboration
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