Results 71 to 80 of about 21,648 (265)
Two knowledge-based methods for High-Performance Sense Distribution Learning [PDF]
, 2018 Knowing the correct distribution of senses within a corpus can potentially boost the performance of Word Sense Disambiguation (WSD) systems by many points.
Navigli, Roberto, Pasini, Tommaso
core +1 more source
Proceedings of the Workshop on Semantic Evaluations: Recent Achievements and Future Directions - DEW '09, 2009 We propose a multilingual unsupervised Word Sense Disambiguation (WSD) task for a sample of English nouns. Instead of providing manually sensetagged examples for each sense of a polysemous noun, our sense inventory is built up on the basis of the Europarl parallel corpus.
Lefever, Els, Hoste, Veronique
openaire +2 more sources
Improving sentiment analysis with learning concepts from concept, patterns lexicons and negations
Ain Shams Engineering Journal, 2022 The way of expressing sentiment (−ve/+ve) in the form of textual information depends on the way of thinking of human beings. Identifying aspect extraction and sentiment polarity from written texts is a crucial task.
Anima Pradhan +2 more
doaj +1 more source
INRIASAC: Simple Hypernym Extraction Methods [PDF]
, 2015 Given a set of terms from a given domain, how can we structure them into a taxonomy without manual intervention? This is the task 17 of SemEval 2015. Here we present our simple taxonomy structuring techniques which, despite their simplicity, ranked first
Grefenstette, Gregory
core +4 more sources
SemEval-2022 Task 7: Identifying Plausible Clarifications of Implicit and Underspecified Phrases in Instructional Texts [PDF]
International Workshop on Semantic Evaluation, 2023 We describe SemEval-2022 Task 7, a shared task on rating the plausibility of clarifications in instructional texts. The dataset for this task consists of manually clarified how-to guides for which we generated alternative clarifications and collected ...
Michael Roth +2 more
semanticscholar +1 more source
The SemEval-2007 WePS evaluation [PDF]
Proceedings of the 4th International Workshop on Semantic Evaluations - SemEval '07, 2007 This paper presents the task definition, resources, participation, and comparative results for the Web People Search task, which was organized as part of the SemEval-2007 evaluation exercise. This task consists of clustering a set of documents that mention an ambiguous person name according to the actual entities referred to using that name.
Javier Artiles +2 more
openaire +1 more source
SemEval-2021 Task 1: Lexical Complexity Prediction [PDF]
International Workshop on Semantic Evaluation, 2021 This paper presents the results and main findings of SemEval-2021 Task 1 - Lexical Complexity Prediction. We provided participants with an augmented version of the CompLex Corpus (Shardlow et al. 2020).
Matthew Shardlow +3 more
semanticscholar +1 more source
SemEval 2018 Task 2: Multilingual Emoji Prediction [PDF]
Proceedings of The 12th International Workshop on Semantic Evaluation, 2018 This paper describes the results of the first shared task on Multilingual Emoji Prediction, organized as part of SemEval 2018. Given the text of a tweet, the task consists of predicting the most likely emoji to be used along such tweet. Two subtasks were proposed, one for English and one for Spanish, and participants were allowed to submit a system run
Barbieri, Francesco +7 more
openaire +2 more sources
SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter
International Workshop on Semantic Evaluation, 2019 The paper describes the organization of the SemEval 2019 Task 5 about the detection of hate speech against immigrants and women in Spanish and English messages extracted from Twitter.
Valerio Basile +7 more
semanticscholar +1 more source
SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection [PDF]
International Workshop on Semantic Evaluation, 2020 Lexical Semantic Change detection, i.e., the task of identifying words that change meaning over time, is a very active research area, with applications in NLP, lexicography, and linguistics.
Dominik Schlechtweg +4 more
semanticscholar +1 more source