Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/91925
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dc.contributorDepartment of Chinese and Bilingual Studiesen_US
dc.creatorCho, WIen_US
dc.creatorChersoni, Een_US
dc.creatorHsu, YYen_US
dc.creatorHuang, CRen_US
dc.date.accessioned2022-01-18T06:24:43Z-
dc.date.available2022-01-18T06:24:43Z-
dc.identifier.isbn978-1-954085-54-1en_US
dc.identifier.urihttp://hdl.handle.net/10397/91925-
dc.language.isoenen_US
dc.publisherAssociation for Computational Linguistics (ACL)en_US
dc.rights©2021 Association for Computational Linguisticsen_US
dc.rightsACL materials are Copyright © 1963–2021 ACL; other materials are copyrighted by their respective copyright holders. Materials prior to 2016 here are licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 International License. Permission is granted to make copies for the purposes of teaching and research. Materials published in or after 2016 are licensed on a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication TH Cho, W. I., Chersoni, E., Hsu, Y. Y., & Huang, C. R. (2021, August). Modeling the Influence of Verb Aspect on the Activation of Typical Event Locations with BERT. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 (pp. 2922-2929) is available at https://doi.org/10.18653/v1/2021.findings-acl.258en_US
dc.titleModeling the influence of verb aspect on the activation of typical event locations with BERTen_US
dc.typeConference Paperen_US
dc.identifier.spage2922en_US
dc.identifier.epage2929en_US
dc.identifier.doi10.18653/v1/2021.findings-acl.258en_US
dcterms.abstractPrior studies on event knowledge in sentence comprehension have shown that the aspect of the main verb plays an important role in the processing of non-core semantic roles, such as locations: when the aspect of the main verb is imperfective, locations become more salient in the mental representation of the event and are easier for human comprehenders to process.en_US
dcterms.abstractIn our study, we tested the popular language model BERT on two datasets derived from experimental studies to determine whether BERT’s predictions of prototypical event locations were also influenced by aspect. We found that, although BERT efficiently modelled the typicality of locations, it did so independently of the verb aspect. Even when the transformer was forced to focus on the verb phrase by masking the context words in the sentence, the typicality predictions were still accurate; in addition, we found aspect to have a stronger influence on the scores, with locations in the imperfective setting being associated with lower surprisal values.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIn Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, August 1 - 6, 2021, p. 2922-2929. Stroudsburg, PA: Association for Computational Linguistics (ACL), 2021en_US
dcterms.issued2021-
dc.relation.ispartofbookFindings of the Association for Computational Linguistics: ACL-IJCNLP 2021, August 1 - 6, 2021en_US
dc.description.validate202201 bcvcen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumbera1141-n02-
dc.identifier.SubFormID43995-
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
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