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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 11 of 11 1 We Need to Consider Disagreement in Evaluation Basile, Valerio; Fell, Michael; Fornaciari, Tommaso. - : Association for Computational Linguistics, 2021. : country:USA, 2021. : place:Stroudsburg, PA, 2021 BASE Show details 2 Free the Plural: Unrestricted Split-Antecedent Anaphora Resolution ... The 28th International Conference on Computational Linguistics 2020; Moosavi, Nafise Sadat; Paun, Silviu. - : Underline Science Inc., 2020 BASE Show details 3 Phrase Detectives Corpus Version 2 Chamberlain, Jon; Paun, Silviu; Yu, Juntao. - : Linguistic Data Consortium, 2019. : https://www.ldc.upenn.edu, 2019 BASE Show details 4 Phrase Detectives Corpus Version 2 ... Chamberlain, Jon; Paun, Silviu; Yu, Juntao. - : Linguistic Data Consortium, 2019 BASE Show details 5 Crowdsourcing and Aggregating Nested Markable Annotations ... Madge, Chris; Yu, Juntao; Chamberlain, Jon. - : Universität Regensburg, 2019 BASE Show details 6 Crowdsourcing and Aggregating Nested Markable Annotations Madge, Chris; Yu, Juntao; Chamberlain, Jon. - : Association for Computational Linguistics, 2019 BASE Show details 7 A Crowdsourced Corpus of Multiple Judgments and Disagreement on Anaphoric Interpretation Paun, Silviu; Uma, Alexandra; Poesio, Massimo; Chamberlain, Jon; Kruschwitz, Udo; Yu, Juntao. - : Association for Computational Linguistics, 2019 Abstract: We present a corpus of anaphoric information (coreference) crowdsourced through a game-with-a-purpose. The corpus, containing annotations for about 108,000 markables, is one of the largest corpora for coreference for English, and one of the largest crowdsourced NLP corpora, but its main feature is the large number of judgments per markable: 20 on average, and over 2.2M in total. This characteristic makes the corpus a unique resource for the study of disagreements on anaphoric interpretation. A second distinctive feature is its rich annotation scheme, covering singletons, expletives, and split-antecedent plurals. Finally, the corpus also comes with labels inferred using a recently proposed probabilistic model of annotation for coreference. The labels are of high quality and make it possible to successfully train a state of the art coreference resolver, including training on singletons and non-referring expressions. The annotation model can also result in more than one label, or no label, being proposed for a markable, thus serving as a baseline method for automatically identifying ambiguous markables. A preliminary analysis of the results is presented. URL: http://repository.essex.ac.uk/25795/ https://doi.org/10.18653/v1/N19-1176 http://repository.essex.ac.uk/25795/7/N19-1176.pdf BASE Hide details 8 Crowdsourcing and Aggregating Nested Markable Annotations Poesio, Massimo; Yu, Juntao; Chamberlain, Jon. - : Association for Computational Linguistics, 2019 BASE Show details 9 A Crowdsourced Corpus of Multiple Judgments and Disagreement on Anaphoric Interpretation Poesio, Massimo; Chamberlain, Jon; Paun, Silviu. - : Association for Computational Linguistics, 2019 BASE Show details 10 Comparing Bayesian Models of Annotation Paun, Silviu; Carpenter, Bob; Hovy, Dirk. - : Association for Computational Linguistics, 2018 BASE Show details 11 A Probabilistic Annotation Model for Crowdsourcing Coreference Kruschwitz, Udo; Chamberlain, Jon; Yu, Juntao. - : Association for Computational Linguistics, 2018 BASE Show details

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