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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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| 2 |
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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| 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 ...
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| 13 |
Anaphoric Zero Pronoun Identification: A Multilingual Approach ...
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Abstract:
Pro-drop languages such as Arabic, Chinese, Italian or Japanese allow morphologically null but referential arguments in certain syntactic positions, called anaphoric zero-pronouns. Much NLP work on anaphoric zero-pronouns (AZP) is based on gold mentions, but models for their identification are a fundamental prerequisite for their resolution in real-life applications. Such identification requires complex language understanding and knowledge of real-world entities. Transfer learning models, such as BERT, have recently shown to learn surface, syntactic, and semantic information,which can be very useful in recognizing AZPs. We propose a BERT-based multilingual model for AZP identification from predicted zero pronoun positions, and evaluate it on the Arabic and Chinese portions of OntoNotes 5.0. As far as we know, this is the first neural network model of AZP identification for Arabic; and our approach outperforms the state-of-the-art for Chinese. Experiment results suggest that BERT implicitly encode information ...
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Keyword:
Computer and Information Science; Digital Media; Engineering; Information and Knowledge Engineering; Natural Language Processing; Neural Network
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URL: https://underline.io/lecture/6575-anaphoric-zero-pronoun-identification-a-multilingual-approach
https://dx.doi.org/10.48448/ysaj-n577
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| 14 |
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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| 19 |
A Crowdsourced Corpus of Multiple Judgments and Disagreement on Anaphoric Interpretation
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