Results 11 to 20 of about 3,813 (211)
SemEval-2023 Task 12: Sentiment Analysis for African Languages (AfriSenti-SemEval)
Proceedings of the The 17th International Workshop on Semantic Evaluation (SemEval-2023), 2023 We present the first Africentric SemEval Shared task, Sentiment Analysis for African Languages (AfriSenti-SemEval) - The dataset is available at https://github.com/afrisenti-semeval/afrisent-semeval-2023. AfriSenti-SemEval is a sentiment classification challenge in 14 African languages: Amharic, Algerian Arabic, Hausa, Igbo, Kinyarwanda, Moroccan ...
Shamsuddeen Hassan Muhammad +9 more
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Proceedings of the 4th International Workshop on Semantic Evaluations - SemEval '07, 2007 The SemEval-2007 task to disambiguate prepositions was designed as a lexical sample task. A set of over 25,000 instances was developed, covering 34 of the most frequent English prepositions, with two-thirds of the instances for training and one-third as the test set.
Ken Litkowski, Orin Hargraves
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Proceedings of the 4th International Workshop on Semantic Evaluations - SemEval '07, 2007 The TempEval task proposes a simple way to evaluate automatic extraction of temporal relations. It avoids the pitfalls of evaluating a graph of inter-related labels by defining three sub tasks that allow pairwise evaluation of temporal relations. The task not only allows straightforward evaluation, it also avoids the complexities of full temporal ...
Marc Verhagen +5 more
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Proceedings of the 4th International Workshop on Semantic Evaluations - SemEval '07, 2007 We provide an overview of the metonymy resolution shared task organised within SemEval-2007. We describe the problem, the data provided to participants, and the evaluation measures we used to assess performance. We also give an overview of the systems that have taken part in the task, and discuss possible directions for future work.
K. Markert, NISSIM, MALVINA
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SemEval-2015 Task 8: SpaceEval [PDF]
Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015), 2015 Human languages exhibit a variety of strategies for communicating spatial information, including toponyms, spatial nominals, locations that are described in relation to other locations, and movements along paths. SpaceEval is a combined information extraction and classification task with the goal of identifying and categorizing such spatial information.
Pustejovsky, James +5 more
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Proceedings of the 4th International Workshop on Semantic Evaluations - SemEval '07, 2007 The "Affective Text" task focuses on the classification of emotions and valence (positive/negative polarity) in news headlines, and is meant as an exploration of the connection between emotions and lexical semantics. In this paper, we describe the data set used in the evaluation and the results obtained by the participating systems.
Strapparava C, Mihalcea R
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Proceedings of the Workshop on Semantic Evaluations: Recent Achievements and Future Directions - DEW '09, 2009 In this paper we describe the SemEval-2010 Cross-Lingual Lexical Substitution task, which is based on the English Lexical Substitution task run at SemEval-2007. In the English version of the task, annotators and systems had to find an alternative substitute word or phrase for a target word in context.
Ravi Sinha +2 more
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Proceedings of the 4th International Workshop on Semantic Evaluations - SemEval '07, 2007 This paper presents the task definition, resources, and the single participant system for Task 12: Turkish Lexical Sample Task (TLST), which was organized in the SemEval-2007 evaluation exercise. The methodology followed for developing the specific linguistic resources necessary for the task has been described in this context.
Zeynep Orhan +2 more
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Proceedings of the 4th International Workshop on Semantic Evaluations - SemEval '07, 2007 In this paper we describe the English Lexical Substitution task for SemEval. In the task, annotators and systems find an alternative substitute word or phrase for a target word in context. The task involves both finding the synonyms and disambiguating the context. Participating systems are free to use any lexical resource.
D. MCCARTHY, NAVIGLI, ROBERTO
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SemEval-2021 Task 12: Learning with Disagreements [PDF]
Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021), 2021 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 assume that a single preferred interpretation exists for each item, which is at best an idealization.
Uma, Alexandra +7 more
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