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• W2468996921 abstract "This paper presents our approach towards the SemEval-2016 Task 10 - Detecting Minimal Semantic Units and their Meanings. Systems are expected to provide a representation of lexical semantics by (1) segmenting tokens into words and multiword units and (2) providing a supersense tag for segments that function as nouns or verbs. Our pipeline rule-based system uses no external resources and was implemented using the mwetoolkit. First, we extract and filter known MWEs from the training corpus. Second, we group input tokens of the test corpus based on this lexicon, with special treatment for non-contiguous expressions. Third, we use an MWE-aware predominant-sense heuristic for supersense tagging. We obtain an F-score of 51.48% for MWE identification and 49.98% for supersense tagging." @default.
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• W2468996921 date "2016-01-01" @default.
• W2468996921 modified "2023-09-24" @default.
• W2468996921 title "UFRGSandLIF at SemEval-2016 Task 10: Rule-Based MWE Identification and Predominant-Supersense Tagging" @default.
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• W2468996921 doi "https://doi.org/10.18653/v1/s16-1140" @default.
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