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dc.contributorDepartment of Computingen_US
dc.contributorDepartment of Chinese and Bilingual Studiesen_US
dc.creatorXiang, Ren_US
dc.creatorGu, Jen_US
dc.creatorChersoni, Een_US
dc.creatorLi, Wen_US
dc.creatorLu, Qen_US
dc.creatorHuang, CRen_US
dc.date.accessioned2024-04-15T07:34:38Z-
dc.date.available2024-04-15T07:34:38Z-
dc.identifier.isbn978-1-954085-70-1en_US
dc.identifier.urihttp://hdl.handle.net/10397/105486-
dc.descriptionSemEval-2021: The 15th International Workshop on Semantic Evaluation, August 5-6, 2021, Bangkok, Thailand (online)en_US
dc.language.isoenen_US
dc.publisherAssociation for Computational Linguistics (ACL)en_US
dc.rights©2021 Association for Computational Linguisticsen_US
dc.rightsThis publication is licensed on a Creative Commons Attribution 4.0 International License. (https://creativecommons.org/licenses/by/4.0/)en_US
dc.rightsThe following publication Rong Xiang, Jinghang Gu, Emmanuele Chersoni, Wenjie Li, Qin Lu, and Chu-Ren Huang. 2021. PolyU CBS-Comp at SemEval-2021 Task 1: Lexical Complexity Prediction (LCP). In Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021), pages 565–570, Online. Association for Computational Linguistics is available at https://doi.org/10.18653/v1/2021.semeval-1.70.en_US
dc.titlePolyU CBS-Comp at SemEval-2021 Task 1 : Lexical Complexity Prediction (LCP)en_US
dc.typeConference Paperen_US
dc.identifier.spage565en_US
dc.identifier.epage570en_US
dc.identifier.doi10.18653/v1/2021.semeval-1.70en_US
dcterms.abstractIn this contribution, we describe the system presented by the PolyU CBS-Comp Team at the Task 1 of SemEval 2021, where the goal was the estimation of the complexity of words in a given sentence context. Our top system, based on a combination of lexical, syntactic, word embeddings and Transformers-derived features and on a Gradient Boosting Regressor, achieves a top correlation score of 0.754 on the subtask 1 for single words and 0.659 on the subtask 2 for multiword expressions.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIn Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021), p. 565-570. Stroudsburg, PA, USA: Association for Computational Linguistics (ACL), 2021en_US
dcterms.issued2021-
dc.relation.ispartofbookProceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)en_US
dc.relation.conferenceInternational Workshops on Semantic Evaluation [SemEval]en_US
dc.description.validate202402 bcchen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberCOMP-0142-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextHong Kong Polytechnic University Postdoctoral Fellowships Scheme Projectsen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS51519549-
dc.description.oaCategoryCCen_US
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