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Exploring the Representations of Individual Entities in the Brain Combining EEG and Distributional Semantics
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In: Front Artif Intell (2022)
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Coreference Resolution for the Biomedical Domain: A Survey ...
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Patterns of Lexical Ambiguity in Contextualised Language Models ...
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Patterns of Polysemy and Homonymy in Contextualised Language Models ...
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SemEval-2021 Task 12: Learning with Disagreements
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Abstract:
Disagreement between coders is ubiquitous in virtually all datasets annotated with human judgements in both natural language processing and computer vision. However, most supervised machine learning methods assume that a single preferred interpretation exists for each item, which is at best an idealization. The aim of the SemEval-2021 shared task on learning with disagreements (Le-Wi-Di) was to provide a unified testing framework for methods for learning from data containing multiple and possibly contradictory annotations covering the best-known datasets containing information about disagreements for interpreting language and classifying images. In this paper we describe the shared task and its results.
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URL: http://repository.essex.ac.uk/31851/1/2021.semeval-1.41.pdf http://repository.essex.ac.uk/31851/ https://doi.org/10.18653/v1/2021.semeval-1.41
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Assessing Polyseme Sense Similarity through Co-predication Acceptability and Contextualised Embedding Distance ...
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Free the Plural: Unrestricted Split-Antecedent Anaphora Resolution ...
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Anaphoric Zero Pronoun Identification: A Multilingual Approach ...
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Fake Opinion Detection: How Similar are Crowdsourced Datasets to Real Data?
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Crowdsourcing and Aggregating Nested Markable Annotations ...
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A Crowdsourced Corpus of Multiple Judgments and Disagreement on Anaphoric Interpretation
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