WHUNlp at SemEval-2016 Task DiMSUM: A Pilot Study in Detecting Minimal Semantic Units and their Meanings using Supervised Models
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Feature EngineeringMachine TranslationSemantic ParsingSimilar Papers 제목 키워드 기반
SemEval-2016 Task 10: Detecting Minimal Semantic Units and their Meanings (DiMSUM)
2016-06-01 · SEMEVAL 2016 6
· Nathan Schneider, Dirk Hovy, Anders Johannsen, Marine Carpuat
Part-Of-Speech TaggingWord Sense Disambiguation
From Incremental Meaning to Semantic Unit (phrase by phrase)
2016-04-17
· Andreas Scherbakov, Ekaterina Vylomova, Fei Liu, Timothy Baldwin
This paper describes an experimental approach to Detection of Minimal Semantic Units and their Meaning (DiMSUM), explored within the framework of SemEval 2016 Task 10. The approach is primarily based on a combination of …
Word EmbeddingsBERT(s) to Detect Multiword Expressions
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Multiword expressions (MWEs) present groups of words in which the meaning of the whole is not derived from the meaning of its parts. The task of processing MWEs is crucial in many natural language processing (NLP) applic…
Machine TranslationTranslationSemEval-2012 Task 6: A Pilot on Semantic Textual Similarity
2012-07-01 · SEMEVAL 2012 7
· Eneko Agirre, Daniel Cer, Mona Diab, Aitor Gonzalez-Agirre
Coreference ResolutionMachine TranslationNatural Language InferenceQuestion Answering+4
SemEval-2015 Task 2: Semantic Textual Similarity, English, Spanish and Pilot on Interpretability
2015-06-01 · SEMEVAL 2015 6
· Eneko Agirre, Carmen Banea, Claire Cardie, Daniel Cer 외
Natural Language InferenceQuestion AnsweringSemantic Textual SimilarityTask 2