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1
Exploring the Representations of Individual Entities in the Brain Combining EEG and Distributional Semantics
In: Front Artif Intell (2022)
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2
Coreference Resolution for the Biomedical Domain: A Survey ...
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3
SemEval 2021 Task 12: Learning with Disagreement ...
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4
Patterns of Lexical Ambiguity in Contextualised Language Models ...
Haber, Janosch; Poesio, Massimo. - : arXiv, 2021
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5
Patterns of Polysemy and Homonymy in Contextualised Language Models ...
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6
Data Augmentation Methods for Anaphoric Zero Pronouns ...
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7
SemEval-2021 Task 12: Learning with Disagreements
Uma, Alexandra; Fornaciari, Tommaso; Dumitrache, Anca. - : Association for Computational Linguistics, 2021
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8
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
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9
Fake opinion detection: how similar are crowdsourced datasets to real data? [<Journal>]
Fornaciari, Tommaso [Verfasser]; Cagnina, Leticia [Verfasser]; Rosso, Paolo [Verfasser].
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10
Neural Coreference Resolution for Arabic ...
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11
Assessing Polyseme Sense Similarity through Co-predication Acceptability and Contextualised Embedding Distance ...
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12
Free the Plural: Unrestricted Split-Antecedent Anaphora Resolution ...
Abstract: Now that the performance of coreference resolvers on the simpler forms of anaphoric reference has greatly improved, more attention is devoted to more complex aspects of anaphora. One limitation of virtually all coreference resolution models is the focus on single-antecedent anaphors. Plural anaphors with multiple antecedents–so-called split-antecedent anaphors (as in John met Mary. They went to the movies)–have not been widely studied in NLP, because they are not annotated in ONTONOTES and are relatively infrequent in other corpora. In this paper, we introduce the first model for unrestricted resolution of split-antecedent anaphors. We start with a strong baseline enhanced by BERT embeddings, and show that we can substantially improve its performance by addressing the sparsity issue. We experiment with auxiliary corpora where split-antecedent anaphors were annotated by the crowd, and with transfer learning models using element-of bridging references and single-antecedent coreference as auxiliary tasks. ...
Keyword: Computer and Information Science; Natural Language Processing; Neural Network
URL: https://dx.doi.org/10.48448/gdn3-dm76
https://underline.io/lecture/6239-free-the-plural-unrestricted-split-antecedent-anaphora-resolution
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13
Anaphoric Zero Pronoun Identification: A Multilingual Approach ...
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14
Fake Opinion Detection: How Similar are Crowdsourced Datasets to Real Data?
Fornaciari, Tommaso; Cagnina, Leticia; Rosso, Paolo. - : Springer-Verlag, 2020
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15
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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16
Phrase Detectives Corpus Version 2 ...
Chamberlain, Jon; Paun, Silviu; Yu, Juntao. - : Linguistic Data Consortium, 2019
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17
Crowdsourcing and Aggregating Nested Markable Annotations ...
Madge, Chris; Yu, Juntao; Chamberlain, Jon. - : Universität Regensburg, 2019
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18
Crowdsourcing and Aggregating Nested Markable Annotations
Madge, Chris; Yu, Juntao; Chamberlain, Jon. - : Association for Computational Linguistics, 2019
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19
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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20
Crowdsourcing and Aggregating Nested Markable Annotations
Poesio, Massimo; Yu, Juntao; Chamberlain, Jon. - : Association for Computational Linguistics, 2019
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