汉语篇章级小句关系的标注体系  

Intra-Sentence Relationship Annotation Scheme for Chinese Discourse Analysis

作　　者：吴云芳[1] 徐艺峰[1] 王恺然 

机构地区：[1]计算语言学教育部重点实验室(北京大学),北京100871

出　　处：《中文信息学报》2015年第3期71-81,共11页Journal of Chinese Information Processing

基　　金：国家自然科学基金(61371129);国家重点基础研究发展计划(2014CB340504);国家社科基金重大项目(12&ZD227);网络文化与数字传播北京市重点实验室开放课题(ICDD201402;ICDD201302)

摘　　要：句际关系自动分析属于篇章语义学研究的范畴,虽然英语句际关系的研究已有大量工作,但汉语句际关系的自动分析还只是刚刚起步。该文在RST理论框架下,结合汉语特点,提出了完整的汉语篇章级小句关系标注体系。将汉语话题和逻辑关系置于同一个框架下进行描述,将小句关系划分为事件附属关系和事件逻辑关系两大类。逻辑关系又包括6个中类、15个小类。目前已在人民日报语料上完成了8 000个句子的小句关系标注。抽取出其中1 000个句子检测了双盲标注的一致性,揭示了汉语意合性语言小句关系标注的困难;并基于标注数据对关系类型进行了定量分析,指示了汉语句际关系自动分析将面临的重点和难点。Automatic discourse analysis has aroused strong interests in the recent years. Compared to the bulks of work on English discourse analysis, much less work has been clone in Chinese discourse parsing. A non-negligible reason is that there is no well-annotated Chinese discourse corpus publically available. Under the RST-framework, this paper proposes an intra-sentence relationship annotation scheme for Chinese discourse analysis. We consider both the topic and the logic aspect, discriminating the attachment relationship and logic relationship in Chinese intra- sentence relationship. The logic relationship consists of 6 types and 15 subtypes. Up to now, we have annotated 8,000 sentences in the People Daily News. We check 1,000 sentences in a double-blind manner for the inter-anno- tator agreement, which may give a hint for the difficulties in this task. Based on the annotated data, we give some statistics analysis and demonstrate some challenges for Chinese automatic discourse analysis.

关 键 词：句际关系 小句关系 语料库标注 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]