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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 3 of 3 1 Multilingual and Cross-lingual Word-in-Context Disambiguation (MCL-WiC) ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Martelli, Federico. - : Underline Science Inc., 2021 BASE Show details 2 SemEval-2021 Task 2: Multilingual and Cross-lingual Word-in-Context Disambiguation (MCL-WiC) ... Martelli, Federico; Kalach, Najla; Tola, Gabriele. - : Zenodo, 2021 BASE Show details 3 SemEval-2021 Task 2: Multilingual and Cross-lingual Word-in-Context Disambiguation (MCL-WiC) ... Martelli, Federico; Kalach, Najla; Tola, Gabriele; Navigli, Roberto. - : Zenodo, 2021 Abstract: SemEval-2021 Task 2: Multilingual and Cross-lingual Word-in-Context Disambiguation (MCL-WiC) Task Description Multilingual and Cross-lingual Word-in-Context Disambiguation (MCL-WiC) is the first SemEval task for Word-in-Context disambiguation which tackles the challenge of capturing the polysemous nature of words without relying on a fixed sense inventory in a multilingual and cross-lingual setting. MCL-WiC provides a single high-quality framework for the performance evaluation of a wide range of approaches aimed at evaluating the capability of a system to deeply understand word meaning . Compared to other datasets, MCL-WiC brings the following novelties: it addresses multilinguality and cross-linguality, it provides coverage of all parts of speech , and it covers a high number of domains and genres . Participating systems will be asked to perform a binary classification task in which they indicate whether the target word is used in the same meaning (tagged as T for true) or in a different meaning (F for ... Keyword: SemEval-2021, Word in Context, Word Sense Disambiguation, Machine Learning, Multilinguality; strategies, tools, standards for lexicographic resources objective 3; WP3 URL: https://zenodo.org/record/5144514 https://dx.doi.org/10.5281/zenodo.5144514 BASE Hide details

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