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UFRGS&LIF at SemEval-2016 task 10: Rule-based MWE identification and predominant-supersense tagging
Cordeiro, S.R.; Ramisch, C.; Villavicencio, A.. - : Association for Computational Linguistics, 2016
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.
URL: http://eprints.whiterose.ac.uk/153561/
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2
How naked is the naked truth? A multilingual lexicon of nominal compound compositionality
Villavicencio, A.; Wilkens, R.; Ramisch, C.. - : Association for Computational Linguistics, 2016
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3
Verblexpor: A lexical resource with semantic roles for Portuguese
Villavicencio, A.; Finatto, M.J.B.; Zilio, L.. - : European Language Resources Association (ELRA), 2016
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4
Filtering and measuring the intrinsic quality of human compositionality judgments
Ramisch, C.; Cordeiro, S.; Villavicencio, A.. - : Association for Computational Linguistics, 2016
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5
Multiword expressions in child language
Wilkens, R.; Idiart, M.; Villavicencio, A.. - : European Language Resources Association (ELRA), 2016
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6
mwetoolkit+sem: Integrating word embeddings in the mwetoolkit for semantic MWE processing
Cordeiro, S.; Ramisch, C.; Villavicencio, A.. - : European Language Resources Association (ELRA), 2016
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7
B2SG: a TOEFL-like task for Portuguese
Wilkens, R.; Zilio, L.; Ferreira, E.. - : European Language Resources Association (ELRA), 2016
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8
Predicting the compositionality of nominal compounds: Giving word embeddings a hard time
Cordeiro, S.; Ramisch, C.; Idiart, M.. - : Association for Computational Linguistics, 2016
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9
Matrix factorization using window sampling and negative sampling for improved word representations
Salle, A.; Idiart, M.; Villavicencio, A.. - : Association for Computational Linguistics, 2016
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