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Jibes & Delights: A Dataset of Targeted Insults and Compliments to Tackle Online Abuse ...
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ViTA: Visual-Linguistic Translation by Aligning Object Tags ...
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HASOCOne@FIRE-HASOC2020: Using BERT and Multilingual BERT models for Hate Speech Detection ...
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Multilingual Pre-Trained Transformers and Convolutional NN Classification Models for Technical Domain Identification ...
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gundapusunil at SemEval-2020 Task 9: Syntactic Semantic LSTM Architecture for SENTIment Analysis of Code-MIXed Data ...
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A SentiWordNet Strategy for Curriculum Learning in Sentiment Analysis ...
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Word Level Language Identification in English Telugu Code Mixed Data ...
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A Sentiwordnet Strategy for Curriculum Learning in Sentiment Analysis
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In: Natural Language Processing and Information Systems (2020)
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Conversational implicatures in English dialogue: Annotated dataset ...
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Abstract:
Human dialogue often contains utterances having meanings entirely different from the sentences used and are clearly understood by the interlocutors. But in human-computer interactions, the machine fails to understand the implicated meaning unless it is trained with a dataset containing the implicated meaning of an utterance along with the utterance and the context in which it is uttered. In linguistic terms, conversational implicatures are the meanings of the speaker's utterance that are not part of what is explicitly said. In this paper, we introduce a dataset of dialogue snippets with three constituents, which are the context, the utterance, and the implicated meanings. These implicated meanings are the conversational implicatures. The utterances are collected by transcribing from listening comprehension sections of English tests like TOEFL (Test of English as a Foreign Language) as well as scraping dialogues from movie scripts available on IMSDb (Internet Movie Script Database). The utterances are ... : 8 Pages, NLP'19 Short paper ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.1911.10704 https://arxiv.org/abs/1911.10704
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BCSAT : A Benchmark Corpus for Sentiment Analysis in Telugu Using Word-level Annotations ...
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Automatic Target Recovery for Hindi-English Code Mixed Puns ...
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Towards Automation of Sense-type Identification of Verbs in OntoSenseNet(Telugu) ...
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Towards Enhancing Lexical Resource and Using Sense-annotations of OntoSenseNet for Sentiment Analysis ...
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Context and Humor: Understanding Amul advertisements of India ...
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