MuCPAD: A Multi-Domain Chinese Predicate-Argument Dataset

Yahui Liu, Haoping Yang, Chen Gong, Qingrong Xia, Zhenghua Li, Min Zhang


Abstract
During the past decade, neural network models have made tremendous progress on in-domain semantic role labeling (SRL). However, performance drops dramatically under the out-of-domain setting. In order to facilitate research on cross-domain SRL, this paper presents MuCPAD, a multi-domain Chinese predicate-argument dataset, which consists of 30,897 sentences and 92,051 predicates from six different domains. MuCPAD exhibits three important features. 1) Based on a frame-free annotation methodology, we avoid writing complex frames for new predicates. 2) We explicitly annotate omitted core arguments to recover more complete semantic structure, considering that omission of content words is ubiquitous in multi-domain Chinese texts. 3) We compile 53 pages of annotation guidelines and adopt strict double annotation for improving data quality. This paper describes in detail the annotation methodology and annotation process of MuCPAD, and presents in-depth data analysis. We also give benchmark results on cross-domain SRL based on MuCPAD.
Anthology ID:
2022.naacl-main.123
Volume:
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Month:
July
Year:
2022
Address:
Seattle, United States
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1707–1717
Language:
URL:
https://aclanthology.org/2022.naacl-main.123
DOI:
10.18653/v1/2022.naacl-main.123
Bibkey:
Cite (ACL):
Yahui Liu, Haoping Yang, Chen Gong, Qingrong Xia, Zhenghua Li, and Min Zhang. 2022. MuCPAD: A Multi-Domain Chinese Predicate-Argument Dataset. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 1707–1717, Seattle, United States. Association for Computational Linguistics.
Cite (Informal):
MuCPAD: A Multi-Domain Chinese Predicate-Argument Dataset (Liu et al., NAACL 2022)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingestion-script-update/2022.naacl-main.123.pdf
Video:
 https://preview.aclanthology.org/ingestion-script-update/2022.naacl-main.123.mp4
Code
 suda-la/mucpad
Data
FrameNet