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Enhanced Labelling in Active Learning for Coreference Resolution ...
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Predicting Coreference in Abstract Meaning Representations ...
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NILC at SR'20: Exploring Pre-Trained Models in Surface Realisation ...
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Persuasiveness of News Editorials depending on Ideology and Personality ...
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E.T.: Entity-Transformers. Coreference augmented Neural Language Model for richer mention representations via Entity-Transformer blocks ...
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TwiConv: A Coreference-annotated Corpus of Twitter Conversations ...
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Resolving Pronouns in Twitter Streams: Context can Help! ...
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Matching Theory and Data with Personal-ITY: What a Corpus of Italian YouTube Comments Reveals About Personality ...
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IMSurReal Too: IMS at the Surface Realization Shared Task 2020 ...
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Multilingual Emoticon Prediction of Tweets about COVID-19 ...
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BME-TUW at SR’20: Lexical grammar induction for surface realization ...
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It's absolutely divine! Can fine-grained sentiment analysis benefit from coreference resolution? ...
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Integrating knowledge graph embeddings to improve mention representation for bridging anaphora resolution ...
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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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