MuCPAD: A Multi-Domain Chinese Predicate-Argument Dataset

Anonymous

Paper Link: https://openreview.net/forum?id=Ye4URhEM4kR

Paper Type: Long paper (up to eight pages of content + unlimited references and appendices)

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.

Presentation Mode: This paper will be presented virtually

Copyright Consent Signature (type Name Or NA If Not Transferrable): Yahui Liu

Copyright Consent Name And Address: Soochow University; Soochow, Jiangsu Province, China