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The Causal News Corpus: Annotating Causal Relations in Event Sentences from News ...
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The corpora they are a-changing: a case study in Italian newspapers
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In: Basile, Pierpaolo orcid:0000-0002-0545-1105 , Caputo, Annalina orcid:0000-0002-7144-8545 , Caselli, Tommaso orcid:0000-0003-2936-0256 , Cassotti, Pierluigi and Varvara, Rossella orcid:0000-0001-9957-2807 (2021) The corpora they are a-changing: a case study in Italian newspapers. In: 2nd International Workshop on Computational Approaches to Historical Language Change 2021, Online. (2021)
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HateBERT: Retraining BERT for Abusive Language Detection in English ...
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Identifying communicative functions in discourse with content types
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In: Lang Resour Eval (2021)
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DIACR-Ita @ EVALITA2020: overview of the EVALITA2020 DiachronicLexical semantics (DIACR-Ita) task
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In: Basile, Pierpaolo, Caputo, Annalina orcid:0000-0002-7144-8545 , Caselli, Tommaso orcid:0000-0003-2936-0256 , Cassotti, Pierluigi and Varvara, Rossella orcid:0000-0001-9957-2807 (2020) DIACR-Ita @ EVALITA2020: overview of the EVALITA2020 DiachronicLexical semantics (DIACR-Ita) task. In: Seventh Evaluation Campaign of Natural Language Processing and Speech Tools for Italian, 17 Dec 2020, Online. (2020)
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A diachronic Italian corpus based on “L’Unit`a”
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In: Basile, Pierpaolo, Caputo, Annalina orcid:0000-0002-7144-8545 , Caselli, Tommaso orcid:0000-0003-2936-0256 , Cassotti, Pierluigi and Varvara, Rossella orcid:0000-0001-9957-2807 (2020) A diachronic Italian corpus based on “L’Unit`a”. In: Seventh Italian Conference on Computational Linguistics, 1-3 Mar 2021, Bologna (Online). (2020)
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On abstraction: decoupling conceptual concreteness and categorical specificity
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In: Cogn Process (2020)
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RuG at GermEval: Detecting Offensive Speech in German Social Media
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In: http://hw.oeaw.ac.at/8435-5 (2018)
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Abstract:
This paper reports on the systems the RuG Team submitted to the GermEval 2018 - Shared Task on the Identification of Offensive Language in German tweets. We submitted three systems to Task 1, targeting the problem as a binary classification task, and only one system for Task 2, addressing a fine-grained classification of offensive tweets in different categories. Preliminary evaluation of the systems has been conducted on a fixed validation set from the training data. The best macro-F1 score for Task 1, binary classification, is 75.45, obtained by an ensemble model composed by a Linear SVM, a CNN, and a Logistic Regressor as a meta-classifier. As for Task 2, multi-class classification, we obtained a macro-F1 of 40.75 using a multi-class Linear SVM.
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Keyword:
Linguistics and Literature
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URL: http://epub.oeaw.ac.at/?arp=buecher/Organisationseinheiten/academiae-corpora/Proceedings%20of%20the%20GermEval%202018Workshop/012_GermEval2018_Proceedings.pdf
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It-TimeML and the Ita-TimeBank: Language Specific Adaptations for Temporal Annotation
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Words in context: a reference perspective on the lexicon ...
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FacTA: Evaluation of Event Factuality and Temporal Anchoring
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State of the Art Language Technologies for Italian: The EVALITA 2014 Perspective
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