Results 21 to 30 of about 21,648 (265)
LLM-RM at SemEval-2023 Task 2: Multilingual Complex NER Using XLM-RoBERTa [PDF]
International Workshop on Semantic Evaluation, 2023 Named Entity Recognition(NER) is a task ofrecognizing entities at a token level in a sen-tence. This paper focuses on solving NER tasksin a multilingual setting for complex named en-tities.Our team, LLM-RM participated in therecently organized SemEval ...
Rahul Mehta, Vasudeva Varma
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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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SemEval-2017 Task 4: Sentiment Analysis in Twitter [PDF]
International Workshop on Semantic Evaluation, 2017 This paper describes the fifth year of the Sentiment Analysis in Twitter task. SemEval-2017 Task 4 continues with a rerun of the subtasks of SemEval-2016 Task 4, which include identifying the overall sentiment of the tweet, sentiment towards a topic with
Sara Rosenthal +2 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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SemEval-2023 Task 10: Explainable Detection of Online Sexism [PDF]
International Workshop on Semantic Evaluation, 2023 Online sexism is a widespread and harmful phenomenon. Automated tools can assist the detection of sexism at scale. Binary detection, however, disregards the diversity of sexist content, and fails to provide clear explanations for why something is sexist.
Hannah Rose Kirk +3 more
semanticscholar +1 more source
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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Multilingual Fine-Grained Named Entity Recognition [PDF]
Computer Science Journal of Moldova, 2023 The “MultiCoNER II Multilingual Complex Named Entity Recognition” task\footnote[1]{\url{https://multiconer.github.io}} within SemEval 2023 competition focuses on identifying complex named entities (NEs), such as the titles of creative works (e.g., songs,
Viorica-Camelia Lupancu, Adrian Iftene
doaj +1 more source
Associating protein residues in the literature with structural data. [PDF]
Acta Crystallogr D Struct BiolA software tool is introduced for associating text mentions of protein residues with their respective residues in a protein structure, with display in a molecular viewer.Protein structures are crucial in understanding the function, mechanism and disease‐causing variants of proteins within any living cell.
Vollmar M +6 more
europepmc +2 more sources
SemEval-2023 Task 1: Visual Word Sense Disambiguation [PDF]
International Workshop on Semantic Evaluation, 2023 This paper presents the Visual Word Sense Disambiguation (Visual-WSD) task.The objective of Visual-WSD is to identify among a set of ten images the one that corresponds to the intended meaning of a given ambiguous word which is accompanied with minimal ...
Alessandro Raganato +4 more
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SemEval-2017 Task 1: Semantic Textual Similarity Multilingual and Crosslingual Focused Evaluation [PDF]
International Workshop on Semantic Evaluation, 2017 Semantic Textual Similarity (STS) measures the meaning similarity of sentences. Applications include machine translation (MT), summarization, generation, question answering (QA), short answer grading, semantic search, dialog and conversational systems ...
Daniel Matthew Cer +4 more
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