@inproceedings{lu-etal-2025-overview,
title = "Overview of {CCL}25-Eval Task6: {C}hinese Essay Rhetoric Recognition Evaluation ({CERRE})",
author = "Lu, Yujiang and
Liu, Nuowei and
Ren, Yupei and
Zhu, Yicheng and
Lan, Man and
Bai, Xiaopeng and
Xu, Mofan and
Liao, Qingyu",
editor = "Lin, Hongfei and
Li, Bin and
Tan, Hongye",
booktitle = "Proceedings of the 24th {C}hina National Conference on Computational Linguistics ({CCL} 2025)",
month = aug,
year = "2025",
address = "Jinan, China",
publisher = "Chinese Information Processing Society of China",
url = "https://aclanthology.org/2025.ccl-2.30/",
pages = "252--260",
abstract = "``Literary grace in Chinese composition writing is a hallmark of linguistic sophistication, often realized through various rhetorical devices. The automatic identification and analysis of rhetorical devices in essays play a crucial role in educational NLP applications, particularly for assessing writing proficiency and facilitating pedagogical interventions. Although prior research has predominantly focused on coarse-grained recognition of limited rhetorical devices at sentence level, these approaches prove inadequate for handling complex rhetorical structures and emerging educational demands. In this paper, we present the CCL25-Eval Task6: Chinese EssayRhetoric Recognition Evaluation (CERRE), a novel framework comprising three distinct evaluation tracks at the document level: (1) Fine-grained Form-level Categories Recognition, (2)Fine-grained Content-level Categories Recognition, and (3) Rhetorical Component Extraction.The evaluation has attracted 29 registered participating teams, with 8 teams submitting valid system outputs. In particular, two participating systems demonstrated superior performance by exceeding the baseline metrics in complete evaluation criteria.''"
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<abstract>“Literary grace in Chinese composition writing is a hallmark of linguistic sophistication, often realized through various rhetorical devices. The automatic identification and analysis of rhetorical devices in essays play a crucial role in educational NLP applications, particularly for assessing writing proficiency and facilitating pedagogical interventions. Although prior research has predominantly focused on coarse-grained recognition of limited rhetorical devices at sentence level, these approaches prove inadequate for handling complex rhetorical structures and emerging educational demands. In this paper, we present the CCL25-Eval Task6: Chinese EssayRhetoric Recognition Evaluation (CERRE), a novel framework comprising three distinct evaluation tracks at the document level: (1) Fine-grained Form-level Categories Recognition, (2)Fine-grained Content-level Categories Recognition, and (3) Rhetorical Component Extraction.The evaluation has attracted 29 registered participating teams, with 8 teams submitting valid system outputs. In particular, two participating systems demonstrated superior performance by exceeding the baseline metrics in complete evaluation criteria.”</abstract>
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%0 Conference Proceedings
%T Overview of CCL25-Eval Task6: Chinese Essay Rhetoric Recognition Evaluation (CERRE)
%A Lu, Yujiang
%A Liu, Nuowei
%A Ren, Yupei
%A Zhu, Yicheng
%A Lan, Man
%A Bai, Xiaopeng
%A Xu, Mofan
%A Liao, Qingyu
%Y Lin, Hongfei
%Y Li, Bin
%Y Tan, Hongye
%S Proceedings of the 24th China National Conference on Computational Linguistics (CCL 2025)
%D 2025
%8 August
%I Chinese Information Processing Society of China
%C Jinan, China
%F lu-etal-2025-overview
%X “Literary grace in Chinese composition writing is a hallmark of linguistic sophistication, often realized through various rhetorical devices. The automatic identification and analysis of rhetorical devices in essays play a crucial role in educational NLP applications, particularly for assessing writing proficiency and facilitating pedagogical interventions. Although prior research has predominantly focused on coarse-grained recognition of limited rhetorical devices at sentence level, these approaches prove inadequate for handling complex rhetorical structures and emerging educational demands. In this paper, we present the CCL25-Eval Task6: Chinese EssayRhetoric Recognition Evaluation (CERRE), a novel framework comprising three distinct evaluation tracks at the document level: (1) Fine-grained Form-level Categories Recognition, (2)Fine-grained Content-level Categories Recognition, and (3) Rhetorical Component Extraction.The evaluation has attracted 29 registered participating teams, with 8 teams submitting valid system outputs. In particular, two participating systems demonstrated superior performance by exceeding the baseline metrics in complete evaluation criteria.”
%U https://aclanthology.org/2025.ccl-2.30/
%P 252-260
Markdown (Informal)
[Overview of CCL25-Eval Task6: Chinese Essay Rhetoric Recognition Evaluation (CERRE)](https://aclanthology.org/2025.ccl-2.30/) (Lu et al., CCL 2025)
ACL
- Yujiang Lu, Nuowei Liu, Yupei Ren, Yicheng Zhu, Man Lan, Xiaopeng Bai, Mofan Xu, and Qingyu Liao. 2025. Overview of CCL25-Eval Task6: Chinese Essay Rhetoric Recognition Evaluation (CERRE). In Proceedings of the 24th China National Conference on Computational Linguistics (CCL 2025), pages 252–260, Jinan, China. Chinese Information Processing Society of China.