Building a Chinese discourse topic corpus with a micro-topic scheme based on theme-rheme theory

Abstract

Background: How to build a suitable discourse topic structure is an important issue in discourse topic analysis, which is the core of natural language understanding. Not only is it the key basic unit to implement automatic computing, but also the key to realize the transformation from unstructured data to structured data during the process of big data analytics. Although the discourse topic structure has wide potential for application in discourse analysis and related tasks, the research on constructing such discourse resources is quite limited in Chinese language. In this paper, we propose a micro-topic scheme (MTS) to represent the discourse topic structure in the Chinese language according to theme-rheme theory, with elementary discourse topic unit(EDTU) as the node and referent of theme-rheme as link. In particular, thematic progression is employed to directly represent the development of the discourse topic structure. Results: Guided by the MTS, we manually annotate a Chinese Discourse Topic Corpus (CDTC) of 500 documents. Moreover, we get 89.9 and 72.15 F1 value in two identification preliminary experiments, respectively, which show that the proposed representation can perform good automatic computation. Conclusion:The lack of the formal representation system and related corpus resources for Chinese discourse topic structure has greatly restricted the study of discourse topic analysis in natural language, and further affected the development of natural language understanding. To address the above issues, a micro-topic scheme(MTS) representation is proposed based on functional grammar theory, and the corresponding corpus resources(i.e., CDTC) are constructed. Our preliminary evaluation justifies the appropriateness of the MTS for Chinese discourse analysis and the usefulness of our CDTC.

EDTC: A Corpus for Discourse-Level Topic Chain Parsing

“…For better understanding of our annotation, we present some preliminary definitions as following: Discourse Topic Unit (DTU) refers to the elementary topic unit in our annotated DTC structure. In the literature, Xi and Zhou (2017) hold the view that each sentence is composed of multiple DTUs with different sub-topics which they refer to as elementary discourse topic unit (EDTU). Different from them, we study macro DTC structures in this work where each sentence is taken as an independent DTU 1 .…”

“…However, the events in the TDT task refer to happenings at certain places and times which only compose a small subset of general topics. Recently, Xi and Zhou (2017) manually annotate the first Chinese DTC corpus based on the theme-rheme theory (Halliday and Matthiessen, 2004). By contrast, due to the lack of corpus, previous study on English DTC parsing usually uses unsupervised methods (Kim and Oh, 2011) to explore the structure and trends of important topics hidden within news articles.…”

“…This research is primarily motivated by (Polanyi and Scha, 1984;Kim and Oh, 2011) on the topic chain concept, (Xi and Zhou, 2017) on DTC corpus construction, and (Reimers et al, 2019) on topic-dependent argument linking. And our contributions mainly include two aspects: (i) building an English corpus of discourse-level topic chain (EDTC) through a two-step annotation method and (ii) lunching a simple but robust Bert-based baseline system for automatic DTC parsing.…”