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SemEval 2021 Task 12: Learning with Disagreement ...
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 assumethat 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) wasto 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. ...
Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
URL: https://underline.io/lecture/30027-semeval-2021-task-12-learning-with-disagreement
https://dx.doi.org/10.48448/jnrq-9d84
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2
Neural Coreference Resolution for Arabic ...
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3
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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