Unsupervised Adverbial Identification in Modern Chinese Literature

Wenxiu Xie; John S. Y. Lee; Fangqiong Zhan; Xiao Han; Chi-Yin Chow

doi:10.18653/v1/2021.latechclfl-1.10

Unsupervised Adverbial Identification in Modern Chinese Literature

Wenxiu Xie, John S. Y. Lee, Fangqiong Zhan, Xiao Han, Chi-Yin Chow

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

2 Citations (Scopus)

Abstract

In many languages, adverbials can be derived from words of various parts-of-speech. In Chinese, the derivation may be marked either with the standard adverbial marker DI, or the non-standard marker DE. Since DE also serves double duty as the attributive marker, accurate identification of adverbials requires disambiguation of its syntactic role. As parsers are trained predominantly on texts using the standard adverbial marker DI, they often fail to recognize adverbials suffixed with the non-standard DE. This paper addresses this problem with an unsupervised, rule-based approach for adverbial identification that utilizes dependency tree patterns. Experiment results show that this approach outperforms a masked language model baseline. We apply this approach to analyze standard and non-standard adverbial marker usage in modern Chinese literature.

Original language	English
Title of host publication	Proceedings of the 5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature
Editors	Stefania Degaetano-Ortlieb, Anna Kazantseva, Nils Reiter, Stan Szpakowicz
Publisher	Association for Computational Linguistics
Pages	91-95
Number of pages	5
ISBN (Print)	9781954085916
DOIs	https://doi.org/10.18653/v1/2021.latechclfl-1.10
Publication status	Published - Nov 2021
Event	5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCHCLfL 2021) - Virtual, Punta Cana, Dominican Republic Duration: 7 Nov 2021 → 11 Nov 2021 https://aclanthology.org/2021.latechclfl-1 https://sighum.wordpress.com/events/latech-clfl-2021/

Publication series

Name	Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, LaTeCHCLfL - Co-located with the Conference on Empirical Methods in Natural Language Processing, EMNLP - Proceedings

Conference

Conference	5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCHCLfL 2021)
Abbreviated title	LaTeCH-CLfL 2021
Country/Territory	Dominican Republic
City	Punta Cana
Period	7/11/21 → 11/11/21
Internet address	https://aclanthology.org/2021.latechclfl-1 https://sighum.wordpress.com/events/latech-clfl-2021/

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10.18653/v1/2021.latechclfl-1.10

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Xie, W., Lee, J. S. Y., Zhan, F., Han, X., & Chow, C.-Y. (2021). Unsupervised Adverbial Identification in Modern Chinese Literature. In S. Degaetano-Ortlieb, A. Kazantseva, N. Reiter, & S. Szpakowicz (Eds.), Proceedings of the 5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (pp. 91-95). (Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, LaTeCHCLfL - Co-located with the Conference on Empirical Methods in Natural Language Processing, EMNLP - Proceedings). Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.latechclfl-1.10

Xie, Wenxiu ; Lee, John S. Y. ; Zhan, Fangqiong et al. / Unsupervised Adverbial Identification in Modern Chinese Literature. Proceedings of the 5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature. editor / Stefania Degaetano-Ortlieb ; Anna Kazantseva ; Nils Reiter ; Stan Szpakowicz. Association for Computational Linguistics, 2021. pp. 91-95 (Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, LaTeCHCLfL - Co-located with the Conference on Empirical Methods in Natural Language Processing, EMNLP - Proceedings).

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title = "Unsupervised Adverbial Identification in Modern Chinese Literature",

abstract = "In many languages, adverbials can be derived from words of various parts-of-speech. In Chinese, the derivation may be marked either with the standard adverbial marker DI, or the non-standard marker DE. Since DE also serves double duty as the attributive marker, accurate identification of adverbials requires disambiguation of its syntactic role. As parsers are trained predominantly on texts using the standard adverbial marker DI, they often fail to recognize adverbials suffixed with the non-standard DE. This paper addresses this problem with an unsupervised, rule-based approach for adverbial identification that utilizes dependency tree patterns. Experiment results show that this approach outperforms a masked language model baseline. We apply this approach to analyze standard and non-standard adverbial marker usage in modern Chinese literature.",

author = "Wenxiu Xie and Lee, {John S. Y.} and Fangqiong Zhan and Xiao Han and Chi-Yin Chow",

year = "2021",

month = nov,

doi = "10.18653/v1/2021.latechclfl-1.10",

language = "English",

isbn = "9781954085916",

series = "Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, LaTeCHCLfL - Co-located with the Conference on Empirical Methods in Natural Language Processing, EMNLP - Proceedings",

publisher = "Association for Computational Linguistics",

pages = "91--95",

editor = "Stefania Degaetano-Ortlieb and Anna Kazantseva and Nils Reiter and Stan Szpakowicz",

booktitle = "Proceedings of the 5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature",

address = "United States",

note = "5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCHCLfL 2021), LaTeCH-CLfL 2021 ; Conference date: 07-11-2021 Through 11-11-2021",

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Xie, W , Lee, JSY , Zhan, F, Han, X & Chow, C-Y 2021, Unsupervised Adverbial Identification in Modern Chinese Literature. in S Degaetano-Ortlieb, A Kazantseva, N Reiter & S Szpakowicz (eds), Proceedings of the 5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature. Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, LaTeCHCLfL - Co-located with the Conference on Empirical Methods in Natural Language Processing, EMNLP - Proceedings, Association for Computational Linguistics, pp. 91-95, 5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCHCLfL 2021), Punta Cana, Dominican Republic, 7/11/21. https://doi.org/10.18653/v1/2021.latechclfl-1.10

Unsupervised Adverbial Identification in Modern Chinese Literature. / Xie, Wenxiu ; Lee, John S. Y.; Zhan, Fangqiong et al.
Proceedings of the 5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature. ed. / Stefania Degaetano-Ortlieb; Anna Kazantseva; Nils Reiter; Stan Szpakowicz. Association for Computational Linguistics, 2021. p. 91-95 (Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, LaTeCHCLfL - Co-located with the Conference on Empirical Methods in Natural Language Processing, EMNLP - Proceedings).

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

TY - GEN

T1 - Unsupervised Adverbial Identification in Modern Chinese Literature

AU - Xie, Wenxiu

AU - Lee, John S. Y.

AU - Zhan, Fangqiong

AU - Han, Xiao

AU - Chow, Chi-Yin

PY - 2021/11

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N2 - In many languages, adverbials can be derived from words of various parts-of-speech. In Chinese, the derivation may be marked either with the standard adverbial marker DI, or the non-standard marker DE. Since DE also serves double duty as the attributive marker, accurate identification of adverbials requires disambiguation of its syntactic role. As parsers are trained predominantly on texts using the standard adverbial marker DI, they often fail to recognize adverbials suffixed with the non-standard DE. This paper addresses this problem with an unsupervised, rule-based approach for adverbial identification that utilizes dependency tree patterns. Experiment results show that this approach outperforms a masked language model baseline. We apply this approach to analyze standard and non-standard adverbial marker usage in modern Chinese literature.

AB - In many languages, adverbials can be derived from words of various parts-of-speech. In Chinese, the derivation may be marked either with the standard adverbial marker DI, or the non-standard marker DE. Since DE also serves double duty as the attributive marker, accurate identification of adverbials requires disambiguation of its syntactic role. As parsers are trained predominantly on texts using the standard adverbial marker DI, they often fail to recognize adverbials suffixed with the non-standard DE. This paper addresses this problem with an unsupervised, rule-based approach for adverbial identification that utilizes dependency tree patterns. Experiment results show that this approach outperforms a masked language model baseline. We apply this approach to analyze standard and non-standard adverbial marker usage in modern Chinese literature.

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U2 - 10.18653/v1/2021.latechclfl-1.10

DO - 10.18653/v1/2021.latechclfl-1.10

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

SN - 9781954085916

T3 - Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, LaTeCHCLfL - Co-located with the Conference on Empirical Methods in Natural Language Processing, EMNLP - Proceedings

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EP - 95

BT - Proceedings of the 5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature

A2 - Degaetano-Ortlieb, Stefania

A2 - Kazantseva, Anna

A2 - Reiter, Nils

A2 - Szpakowicz, Stan

PB - Association for Computational Linguistics

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Xie W , Lee JSY , Zhan F, Han X, Chow CY. Unsupervised Adverbial Identification in Modern Chinese Literature. In Degaetano-Ortlieb S, Kazantseva A, Reiter N, Szpakowicz S, editors, Proceedings of the 5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature. Association for Computational Linguistics. 2021. p. 91-95. (Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, LaTeCHCLfL - Co-located with the Conference on Empirical Methods in Natural Language Processing, EMNLP - Proceedings). doi: 10.18653/v1/2021.latechclfl-1.10

Unsupervised Adverbial Identification in Modern Chinese Literature

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