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Simulating Lexical Semantic Change from Sense-Annotated Data ...
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Shared task: Lexical semantic change detection in German (Student Project Report) ...
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SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection ...
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Swedish Test Data for SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection ...
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LatinISE test data for SemEval 2020 task 1 with additional token versions of the corpora ...
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LatinISE test data for SemEval 2020 task 1 with additional token versions of the corpora ...
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Swedish Test Data for SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection ...
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Swedish Test Data for SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection ...
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SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection ...
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SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection
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Abstract:
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. Evaluation is currently the most pressing problem in Lexical Semantic Change detection, as no gold standards are available to the community, which hinders progress. We present the results of the first shared task that addresses this gap by providing researchers with an evaluation framework and manually annotated, high-quality datasets for English, German, Latin, and Swedish. 33 teams submitted 186 systems, which were evaluated on two subtasks.
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Keyword:
cs.CL
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URL: https://www.repository.cam.ac.uk/handle/1810/309297 https://doi.org/10.17863/CAM.56395
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Time-Out: Temporal Referencing for Robust Modeling of Lexical Semantic Change ...
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A Wind of Change: Detecting and Evaluating Lexical Semantic Change across Times and Domains ...
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Diachronic Usage Relatedness (DURel): A Framework for the Annotation of Lexical Semantic Change ...
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German in Flux: Detecting Metaphoric Change via Word Entropy ...
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Hypernyms under Siege: Linguistically-motivated Artillery for Hypernymy Detection ...
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