Paraphrasing Compound Nominalizations

John S. Y. Lee; Ho Hung Lim; Carol Webster

doi:10.18653/v1/2021.emnlp-main.632

Paraphrasing Compound Nominalizations

John S. Y. Lee, Ho Hung Lim, Carol Webster

Department of Linguistics and Translation

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

3 Citations (Scopus)

58 Downloads (CityUHK Scholars)

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.

Original language	English
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
Pages	8023–8028
ISBN (Electronic)	978-1-955917-09-4, 9781955917094
ISBN (Print)	9781955917094
DOIs	https://doi.org/10.18653/v1/2021.emnlp-main.632
Publication status	Published - Nov 2021
Event	2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021) - Online & in the Barceló Bávaro Convention Centre, Punta Cana, Dominican Republic Duration: 7 Nov 2021 → 11 Nov 2021 https://2021.emnlp.org/ https://aclanthology.org/volumes/2021.emnlp-main/

Publication series

Name	EMNLP 2021 - 2021 Conference on Empirical Methods in Natural Language Processing, Proceedings

Conference

Conference	2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021)
Country/Territory	Dominican Republic
City	Punta Cana
Period	7/11/21 → 11/11/21
Internet address	https://2021.emnlp.org/ https://aclanthology.org/volumes/2021.emnlp-main/

Publisher's Copyright Statement

© 2021 Association for Computational Linguistics. This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

Access Output

10.18653/v1/2021.emnlp-main.632

86028581.pdfFinal Published version, 242 KBLicence: CC BY

https://aclanthology.org/2021.emnlp-main.632/

Other Access Options

Check CityUHK Library

Permanent Link

Right click to copy link

Cite this

Lee, J. S. Y., Lim, H. H., & Webster, C. (2021). Paraphrasing Compound Nominalizations. In M.-F. Moens, X. Huang, L. Specia, & S. W. Yih (Eds.), Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (pp. 8023–8028). (EMNLP 2021 - 2021 Conference on Empirical Methods in Natural Language Processing, Proceedings). Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.emnlp-main.632

Lee, John S. Y. ; Lim, Ho Hung ; Webster, Carol. / Paraphrasing Compound Nominalizations. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. editor / Marie-Francine Moens ; Xuanjing Huang ; Lucia Specia ; Scott Wen-tau Yih. Association for Computational Linguistics, 2021. pp. 8023–8028 (EMNLP 2021 - 2021 Conference on Empirical Methods in Natural Language Processing, Proceedings).

@inproceedings{9a5ce996eada4f518fc372806312c353,

title = "Paraphrasing Compound Nominalizations",

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.",

author = "Lee, {John S. Y.} and Lim, {Ho Hung} and Carol Webster",

year = "2021",

month = nov,

doi = "10.18653/v1/2021.emnlp-main.632",

language = "English",

isbn = "9781955917094",

series = "EMNLP 2021 - 2021 Conference on Empirical Methods in Natural Language Processing, Proceedings",

publisher = "Association for Computational Linguistics",

pages = "8023–8028",

editor = "Marie-Francine Moens and Xuanjing Huang and Lucia Specia and Yih, {Scott Wen-tau}",

booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing",

address = "United States",

note = "2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021) ; Conference date: 07-11-2021 Through 11-11-2021",

url = "https://2021.emnlp.org/, https://aclanthology.org/volumes/2021.emnlp-main/",

}

Lee, JSY, Lim, HH & Webster, C 2021, Paraphrasing Compound Nominalizations. in M-F Moens, X Huang, L Specia & SW Yih (eds), Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. EMNLP 2021 - 2021 Conference on Empirical Methods in Natural Language Processing, Proceedings, Association for Computational Linguistics, pp. 8023–8028, 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021), Punta Cana, Dominican Republic, 7/11/21. https://doi.org/10.18653/v1/2021.emnlp-main.632

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, 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 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Paraphrasing Compound Nominalizations

AU - Lee, John S. Y.

AU - Lim, Ho Hung

AU - Webster, Carol

PY - 2021/11

Y1 - 2021/11

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85127385525&partnerID=8YFLogxK

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85127385525&origin=recordpage

U2 - 10.18653/v1/2021.emnlp-main.632

DO - 10.18653/v1/2021.emnlp-main.632

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781955917094

T3 - EMNLP 2021 - 2021 Conference on Empirical Methods in Natural Language Processing, Proceedings

SP - 8023

EP - 8028

BT - Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

A2 - Moens, Marie-Francine

A2 - Huang, Xuanjing

A2 - Specia, Lucia

A2 - Yih, Scott Wen-tau

PB - Association for Computational Linguistics

T2 - 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021)

Y2 - 7 November 2021 through 11 November 2021

ER -

Lee JSY, Lim HH, Webster C. Paraphrasing Compound Nominalizations. In Moens MF, Huang X, Specia L, Yih SW, editors, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics. 2021. p. 8023–8028. (EMNLP 2021 - 2021 Conference on Empirical Methods in Natural Language Processing, Proceedings). doi: 10.18653/v1/2021.emnlp-main.632

Paraphrasing Compound Nominalizations

Abstract

Publication series

Conference

Publisher's Copyright Statement

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

Cite this