Abstract
Nominalization re-writes a clause as a noun phrase. It requires the transformation of the head verb of the clause into a deverbal noun, and the verb’s modifiers into nominal modifiers. Past research has focused on the selection of deverbal nouns, but has paid less attention to predicting the word positions and word forms for the nominal modifiers. We propose the use of a textual entailment model for clause nominalization. We obtained the best performance by fine-tuning a textual entailment model on this task, outperforming a number of unsupervised approaches using language model scores from a state-of-the-art neural language model.- Anthology ID:
- 2022.coling-1.524
- Volume:
- Proceedings of the 29th International Conference on Computational Linguistics
- Month:
- October
- Year:
- 2022
- Address:
- Gyeongju, Republic of Korea
- Editors:
- Nicoletta Calzolari, Chu-Ren Huang, Hansaem Kim, James Pustejovsky, Leo Wanner, Key-Sun Choi, Pum-Mo Ryu, Hsin-Hsi Chen, Lucia Donatelli, Heng Ji, Sadao Kurohashi, Patrizia Paggio, Nianwen Xue, Seokhwan Kim, Younggyun Hahm, Zhong He, Tony Kyungil Lee, Enrico Santus, Francis Bond, Seung-Hoon Na
- Venue:
- COLING
- SIG:
- Publisher:
- International Committee on Computational Linguistics
- Note:
- Pages:
- 6002–6006
- Language:
- URL:
- https://aclanthology.org/2022.coling-1.524
- DOI:
- Bibkey:
- Cite (ACL):
- John S. Y. Lee, Ho Hung Lim, Carol Webster, and Anton Melser. 2022. Automatic Nominalization of Clauses through Textual Entailment. In Proceedings of the 29th International Conference on Computational Linguistics, pages 6002–6006, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
- Cite (Informal):
- Automatic Nominalization of Clauses through Textual Entailment (Lee et al., COLING 2022)
- Copy Citation:
- PDF:
- https://aclanthology.org/2022.coling-1.524.pdf
Export citation
@inproceedings{lee-etal-2022-automatic,
title = "Automatic Nominalization of Clauses through Textual Entailment",
author = "Lee, John S. Y. and
Lim, Ho Hung and
Webster, Carol and
Melser, Anton",
editor = "Calzolari, Nicoletta and
Huang, Chu-Ren and
Kim, Hansaem and
Pustejovsky, James and
Wanner, Leo and
Choi, Key-Sun and
Ryu, Pum-Mo and
Chen, Hsin-Hsi and
Donatelli, Lucia and
Ji, Heng and
Kurohashi, Sadao and
Paggio, Patrizia and
Xue, Nianwen and
Kim, Seokhwan and
Hahm, Younggyun and
He, Zhong and
Lee, Tony Kyungil and
Santus, Enrico and
Bond, Francis and
Na, Seung-Hoon",
booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
month = oct,
year = "2022",
address = "Gyeongju, Republic of Korea",
publisher = "International Committee on Computational Linguistics",
url = "https://aclanthology.org/2022.coling-1.524",
pages = "6002--6006",
abstract = "Nominalization re-writes a clause as a noun phrase. It requires the transformation of the head verb of the clause into a deverbal noun, and the verb{'}s modifiers into nominal modifiers. Past research has focused on the selection of deverbal nouns, but has paid less attention to predicting the word positions and word forms for the nominal modifiers. We propose the use of a textual entailment model for clause nominalization. We obtained the best performance by fine-tuning a textual entailment model on this task, outperforming a number of unsupervised approaches using language model scores from a state-of-the-art neural language model.",
}
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<abstract>Nominalization re-writes a clause as a noun phrase. It requires the transformation of the head verb of the clause into a deverbal noun, and the verb’s modifiers into nominal modifiers. Past research has focused on the selection of deverbal nouns, but has paid less attention to predicting the word positions and word forms for the nominal modifiers. We propose the use of a textual entailment model for clause nominalization. We obtained the best performance by fine-tuning a textual entailment model on this task, outperforming a number of unsupervised approaches using language model scores from a state-of-the-art neural language model.</abstract>
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%0 Conference Proceedings %T Automatic Nominalization of Clauses through Textual Entailment %A Lee, John S. Y. %A Lim, Ho Hung %A Webster, Carol %A Melser, Anton %Y Calzolari, Nicoletta %Y Huang, Chu-Ren %Y Kim, Hansaem %Y Pustejovsky, James %Y Wanner, Leo %Y Choi, Key-Sun %Y Ryu, Pum-Mo %Y Chen, Hsin-Hsi %Y Donatelli, Lucia %Y Ji, Heng %Y Kurohashi, Sadao %Y Paggio, Patrizia %Y Xue, Nianwen %Y Kim, Seokhwan %Y Hahm, Younggyun %Y He, Zhong %Y Lee, Tony Kyungil %Y Santus, Enrico %Y Bond, Francis %Y Na, Seung-Hoon %S Proceedings of the 29th International Conference on Computational Linguistics %D 2022 %8 October %I International Committee on Computational Linguistics %C Gyeongju, Republic of Korea %F lee-etal-2022-automatic %X Nominalization re-writes a clause as a noun phrase. It requires the transformation of the head verb of the clause into a deverbal noun, and the verb’s modifiers into nominal modifiers. Past research has focused on the selection of deverbal nouns, but has paid less attention to predicting the word positions and word forms for the nominal modifiers. We propose the use of a textual entailment model for clause nominalization. We obtained the best performance by fine-tuning a textual entailment model on this task, outperforming a number of unsupervised approaches using language model scores from a state-of-the-art neural language model. %U https://aclanthology.org/2022.coling-1.524 %P 6002-6006
Markdown (Informal)
[Automatic Nominalization of Clauses through Textual Entailment](https://aclanthology.org/2022.coling-1.524) (Lee et al., COLING 2022)
- Automatic Nominalization of Clauses through Textual Entailment (Lee et al., COLING 2022)
ACL
- John S. Y. Lee, Ho Hung Lim, Carol Webster, and Anton Melser. 2022. Automatic Nominalization of Clauses through Textual Entailment. In Proceedings of the 29th International Conference on Computational Linguistics, pages 6002–6006, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.