Paraphrasing Compound Nominalizations
Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45) › 32_Refereed conference paper (with ISBN/ISSN) › peer-review
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Detail(s)
Original language | English |
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Title of host publication | Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing |
Editors | Marie-Francine Moens, Xuanjing Huang, Lucia Specia, Scott Wen-tau Yih |
Publisher | Association for Computational Linguistics (ACL) |
Pages | 8023–8028 |
ISBN (Electronic) | 978-1-955917-09-4, 9781955917094 |
ISBN (Print) | 9781955917094 |
Publication status | Published - Nov 2021 |
Publication series
Name | EMNLP 2021 - 2021 Conference on Empirical Methods in Natural Language Processing, Proceedings |
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Conference
Title | 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021) |
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Location | Online & in the Barceló Bávaro Convention Centre |
Place | Dominican Republic |
City | Punta Cana |
Period | 7 - 11 November 2021 |
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DOI | DOI |
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Attachment(s) | Documents
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Document Link | Links
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Link to Scopus | https://www.scopus.com/record/display.uri?eid=2-s2.0-85127385525&origin=recordpage |
Permanent Link | https://scholars.cityu.edu.hk/en/publications/publication(9a5ce996-eada-4f51-8fc3-72806312c353).html |
Abstract
A nominalization uses a deverbal noun to describe an event associated with its underlying verb. Commonly found in academic and formal texts, nominalizations can be difficult to interpret because of ambiguous semantic relations between the deverbal noun and its arguments. Our goal is to interpret nominalizations by generating clausal paraphrases. We address compound nominalizations with both nominal and adjectival modifiers, as well as prepositional phrases. In evaluations on a number of unsupervised methods, we obtained the strongest performance by using a pre-trained contextualized language model to re-rank paraphrase candidates identified by a textual entailment model.
Research Area(s)
Citation Format(s)
Paraphrasing Compound Nominalizations. / Lee, John S. Y.; Lim, Ho Hung; Webster, Carol.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. ed. / Marie-Francine Moens; Xuanjing Huang; Lucia Specia; Scott Wen-tau Yih. Association for Computational Linguistics (ACL), 2021. p. 8023–8028 (EMNLP 2021 - 2021 Conference on Empirical Methods in Natural Language Processing, Proceedings).Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45) › 32_Refereed conference paper (with ISBN/ISSN) › peer-review
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