Elamur Research⌕
☰
home / papers / 2018 / MCDTB: A Macro-level Chinese Discourse TreeBank

MCDTB: A Macro-level Chinese Discourse TreeBank

Summary

Most discourse resources, both English and Chinese, focus on micro-level relations within or between sentences. Relations among paragraphs and larger blocks of text remain largely unannotated, especially for Chinese. The authors build MCDTB, a Chinese treebank that labels discourse at the macro level. It follows Rhetorical Structure Theory (RST) and uses paragraphs as the elementary units. Each news article gets a tree that encodes structure, nuclearity and relation type.

Macro-level units are long, their themes are vague, and explicit connectives are absent. To handle this, annotators first identify each unit's theme and judge importance against the writing intention of the whole article, not just the local pair. They also mark supporting information: paragraph topic sentences, the lead and an abstract.

The finished corpus has 720 articles with inter-annotator Kappa above 0.6. Preliminary experiments indicate that the annotations can be learned computationally. The resource supports macro discourse parsing and downstream uses such as automatic summarization.

Key points

  • MCDTB contains 720 annotated Chinese news articles, with inter-annotator agreement (Kappa) above 0.6. Example article IDs such as chtb0155 suggest the texts come from CTB.
  • Nuclearity follows RST and has three labels: Nucleus Ahead and Nucleus Behind (both mononuclear) and Multi-Nucleus. Nuclearity is decided with the global intent of the article in mind.
  • The relation inventory has 3 categories (Coordination, Causality, Elaboration) and 15 relations. It is adapted from CDTB's 4 categories and 17 relations by dropping the Transition category, since such relations are rare at the macro level in news.
  • Besides trees, the corpus marks topic sentences, the lead and an abstract to make the macro annotation more objective.
  • The paper positions MCDTB against RST-DT (385 WSJ articles), PDTB (2,159 articles) and Chinese micro-level corpora (e.g., CDTB with 500 Xinhua articles), none of which cover inter-paragraph relations.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

Fields: Linguistics & languages

Topics: Discourse analysis · Treebanks

Cited by

9 papers of our library cite it (of the 140673 whose bibliographies we read); 3 of them have a page here, 6 not yet.

Cite

The paper itself, not this page. BibTeX from the library's record of the work.

@inproceedings{jiang2018mcdtb,
  title = {{MCDTB: A Macro-level Chinese Discourse TreeBank}},
  author = {Jiang, Feng and Xu, Sheng and Chu, Xiaomin and Li, Peifeng and Zhu, Qiaoming and Zhou, Guodong},
  booktitle = {Proceedings of the 27th International Conference on Computational Linguistics},
  year = {2018},
  url = {https://aclanthology.org/C18-1296/}
}

References

36 references, 6 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

  1. Cohan Arman, and Nazli Goharian. 2015. Scientific article summarization using citation-context and article’s discourse structure. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP 2015). Pages 390-400, Lisbon, Portugal, September. Association for Comput… find
  2. Ezra Black, Steven Abney, Dan Flickinger, C. Gdaniec, R. Grishman, P. Harrison, D. Hindle, R. Ingria, F. Jelinek, J. Klavans, M. Liberman, M. Marcus, S. Roukos, B. Santorini and T. Strzalkowski. 1991. Procedure for quantitatively comparing the syntactic coverage of English grammars. In Proceedings o… find
  3. Xiaomin Chu, Qiaoming Zhu and Guodong Zhou. 2017. Discourse primary-secondary relationships in natural language processing. Chinese Journal of Computers, 40(04): 842-860. find
  4. Teun A. Van Dijk. 1976. Narrative macrostructures. PTL: A journal for descriptive poetics and theory of literature, 1: 547-568. find
  5. Teun A. Van Dijk. 1980. Macrostructure: An interdisciplinary study of global structures in discourse, interaction, and cognition. Hillsdale, New Jersey: Lawrence Erlbaum Associates, Inc., Publishers. find
  6. Teun A. Van Dijk. 1990. News as discourse. Hillsdale, New Jersey: Lawrence Erlbaum Associates, Inc., Publishers. find
  7. Vanessa Wei Feng and Graeme Hirst. 2012. Text-level discourse parsing with rich linguistic features. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers-Volume 1(ACL 2012). Pages 60-68. Jeju, Korea, July. Association for Computational Linguistics. find our card
  8. Vanessa Wei Feng and Graeme Hirst. 2014. A linear-time bottom-up discourse parser with constraints and post-editing. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (ACL 2014). Pages 511-521, Baltimore, USA, June. Association for Computational Linguistics. find our card
  9. Fuyi Fu. Study of complex sentences in Chinese. 2001. Beijing: Commercial Press. find
  10. Xiaoyan Hao, Wei Liu, Ru Li and Kaiying Liu. 2007. Description systems of the Chinese framenet database and software tools. Journal of Chinese Information Processing, 21(5): 96-100. find
  11. Jerry R. Hobbs 1985. On the coherence and structure of discourse. Center for the Study of Language and Information. Pages 1-36. find
  12. Klaus Krippendorff. 1980. Content analysis: An introduction to its methodology. Seikeigeka Orthopedic Surgery, 79(385): 204. find
  13. Feng Jiang, Xiaomin Chu, Sheng Xu, Peifeng Li and Qiaoming Zhu. 2018. A Macro Discourse Primary and Secondary Relation Recognition Method. Journal of Chinese Information Processing, 32 (01): 43-50. find
  14. Jin Li and Kaihong Liao. Comparison of theme patterns and paragraph structures in Chinese and English. 2001. Jinan Journal (Philosophy & Social Science Edition), 23(05): 89-93. find
  15. Yancui Li, Wenhe Feng, Jing Sun, Kong Fang and Guodong Zhou. 2014. Building Chinese discourse corpus with connective-driven dependency tree structure. In Conference on Empirical Methods in Natural Language Processing (EMNLP 2014). Pages 2105-2114. Doha, Qatar, October. Association for Computational… find
  16. Yancui Li. 2015. Research on the structure of Chinese text structure and the construction of resources. Soochow University. find
  17. Yancui Li, Jing Sun and Guodong Zhou. 2015. Automatic recognition and classification on Chinese discourse connective. Acta Scientiarum Naturalium Universitatis Pekinensis, (02): 307-314. find
  18. Jiayi Liu and Yimin Zou. 2017. A review of automatic text summarization research in recent 70 years. Information Science. 35 (07), pages 154-161. find
  19. Guoying Lv, Na Su, Ru Li, Zhiqiang Wang and Qinghua Chai. 2015. Frame-based discourse structure modeling and relation recognition for Chinese sentence. Journal of Chinese Information Processing, 29 (06): 98-109. find
  20. Carlson Lynn, Daniel Marcu and Mary Ellen Okurowski. 2003. Building a discourse-tagged corpus in the framework of rhetorical structure theory. In Current and new directions in discourse and dialogue. Pages 85-112. Springer, Dordrecht. find our card
  21. Maria Liakata, Simon Dobnik, Shyamasree Saha, Colin Batchelor and Dietrich Rebholz-Schuhmann. 2013. A discourse-driven content model for summarising scientific articles evaluated in a complex question answering task. find
  22. In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing (EMNLP 2013). Pages 747-757, Seattle, USA, October. Association for Computational Linguistics. find
  23. William C. Mann and Sandra A. Thompson. 1987. Rhetorical structure theory: a theory of text organization. University of Southern California, Information Sciences Institute. find
  24. William C. Mann, Christian M. I. M. Matthiessen and Sandra A. Thompson. 1992. Rhetorical structure theory and text analysis. Discourse description: Diverse linguistic analysis of a fund-raising text. Pages 39-78. find
  25. Daniel Marcu, Estibaliz Amorrortu and Magdalena Romera. 1999. Experiments in constructing a corpus of discourse trees. In Proceedings of the ACL’99 Workshop on Standards and Tools for Discourse Tagging. Pages 48-57. find
  26. James Robert Martin and David Rose. 2003. Working with discourse: Meaning beyond the clause. London: Continuum. find
  27. Rashmi Prasad, Nikhil Dinesh, Alan Lee and Eleni Miltsakaki. The Penn Discourse Treebank 2.0. 2008. In International Conference on Language Resources and Evaluation, LREC 2008. Marrakech, Morocco, May. Pages 2961-2968. find our card
  28. Sidney Siegel and N. John Castellan. 1988. Nonparametric statistics for the behavioral sciences. 2. New York: McGraw-Hill Book Company. find
  29. Caroline Sporleder and Alex Lascarides. 2004. Combining hierarchical clustering and machine learning to predict high-level discourse structure. In Proceedings of the 20th international conference on Computational Linguistics (Coling 2004). Pages 43. Association for Computing Machinery. find
  30. Yizhong Wang, Sujian Li and Houfeng Wang. 2017. A two-stage parsing method for text-level discourse analysis. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) (ACL 2017), pages 184-188, Vancouver, Canada, July. Association for Comput… find our card
  31. Weizhang Wu and Xiaolin Tian. 2000. Chinese sentence group. Beijing: Commercial Press. find
  32. Shuai Xu. 2009. Research and implementation of paraphrase recognition for question answering. Harbin Institute of Technology. find
  33. Nianwen Xue. 2005. Annotating discourse connectives in the Chinese Treebank. In Proceedings of the Workshop on Frontiers in Corpus Annotations II: Pie in the Sky. Association for Computational Linguistics. Pages 84-91. find our card
  34. Nianwen Xue, Fei Xia, Fudong Chiou and Marta Palmer. 2005. The Penn Chinese Treebank: Phrase structure annotation of a large corpus. Natural language engineering, 11(2): 207-238. find
  35. Yuping Zhou and Nianwen Xue. 2015. The Chinese Discourse TreeBank: a Chinese corpus annotated with discourse relations. Language Resources & Evaluation, 49(2): 397-431. find
  36. Bowei Zou, Guodong Zhou and Qiaoming Zhu. 2014. Negation focus identification with contextual discourse information. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL 2014). Pages 522-530, Baltimore, USA, June. Association for Computational Linguistics. find

↑ back to top

This page in Markdown →