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Analyzing the Structure of Argumentative Discourse

Paper · 1987 · Robin Cohen

Summary

The paper asks how a computer, acting as a listener, can work out the structure of an argument in which a speaker is trying to persuade it. Story understanding can rely on stereotyped content, but arguments cannot. They are always goal-directed, though, and that gives them a logical shape a hearer can exploit. Cohen represents an argument as a tree in which each claim sits above the propositions that support it. The tree is built incrementally, one proposition at a time.

The model separates two questions: where a new proposition attaches, and whether a support relation actually holds. The second is handed to an "evidence oracle" that answers yes or no. Three ideas constrain where a proposition can attach:

  • a theory of expected coherent orderings, which limits the search;
  • the interpretation of clue words such as connectives;
  • pragmatic reasoning that lets the hearer recognize unstated premises the speaker believes but the hearer does not yet hold.

The resulting reception algorithms run in linear time. The work matters as an early, explicitly algorithmic account of recovering discourse structure under differing beliefs.

Key points

  • Three coherent transmission orders are modeled: pre-order (claim before evidence), post-order (evidence before claim) and hybrid (sub-arguments in either order). Each has a reception algorithm shown to be linear in the number of tree nodes.
  • The pre-order algorithm searches for a father up the right border of the tree. The post-order algorithm uses a stack. The hybrid algorithm searches for both a father and sons to re-attach, closing off ineligible nodes as it goes.
  • The proposed system is made up of three modules: an Evidence Oracle, a Clue Interpreter and a Proposition Analyzer. Of these, the oracle relies on a shared knowledge base together with a speaker model that it is able to revise.
  • A Prolog implementation (Smedley 1986) tests only the reception algorithms, with the oracle replaced by queries to the user. Broader validation comes from hand simulations and complexity analysis in Cohen (1983).
  • Future work aims at a general discourse model that recovers linguistic and intentional structure together, in connection with Grosz and Sidner (1986).

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

 Institutions

🎓University of WaterlooWaterloo · Canada67 works · 13,592 citations

 Fields, topics and concepts

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Computer Science · 16,667 worksArtificial Intelligence · 16,194 worksArts and Humanities · 16,039 worksLanguage and Linguistics · 15,891 worksPhilosophy · 284 worksLiterature and Literary Theory · 519 works

🧭 Topics 1Research subjects and languages the work is about.Discourse analysis · 466 works

Cite

Cite as Robin Cohen. 1987. Analyzing the Structure of Argumentative Discourse. Computational Linguistics.

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

@article{cohen1987analyzing,
  title = {{Analyzing the Structure of Argumentative Discourse}},
  author = {Robin Cohen},
  journal = {Computational Linguistics},
  year = {1987},
  url = {https://aclanthology.org/J87-1002/}
}

References

26 references, 0 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

  1. Archbold, A. 1976 A Study of Some Argument Forms in a Persuasion Dialogue. ISI internal document, Marina del Rey, California. find
  2. Archbold, A. and Hobbs, J. 1980 Notes on "The Analysis of Evaluative Argumentation in Text": A Report on On-Going Work. SRI unpublished draft, Menlo Park, California. find
  3. Birnbaum, L.; Flowers, M.; and McGuire, R. 1980 Towards an AI Model of Argumentation. Proceedings of American Association .for Artificial Intelligence (AAAI) Conference: 313-315. find
  4. Cohen, P. 1978 On Knowing What to Say: Planning Speech Acts. Technical Report No. 118, Computer Science Department, University of Toronto, Toronto, Ontario, Canada. find
  5. Cohen, R. 1980 Understanding Arguments. Proceedings of Canadian Society for Computational Studies of Intelligence (CSCSI) Conference: 272-279. find
  6. Cohen, R. 1981 Investigation of Processing Strategies for the Structural Analysis of Arguments. Proceedings of the Association for Computational Linguistics (ACL) Conference: 71-75. find
  7. Cohen, R. 1983 A Computational Model for the Analysis of Arguments. Ph.D. thesis, Technical Report No. 151, Computer Systems Research Group, University of Toronto, Toronto, Ontario, Canada. find
  8. Cohen, R. 1984a A Theory of Discourse Coherence for Argument Understanding. Proceedings of Canadian Society for Computational Studies of lntelligence(CSCSl) Conference: 6-10. find
  9. Cohen, R. 1984b A Computational Theory of the Function of Clue Words in Argument Understanding. Proceedings of lOth International Conference on Computational Linguistics (COLING 84): 251-258. find
  10. Cohen, R. 1985 The Need for Pragmatics in Natural Language Understanding. Proceedings of CSCSI-sponsored Theoretical Advances in Natural Language Understanding Conference. find
  11. Gazdar, G. 1979 Pragmatics: lmplicature. Presupposition and Logical Form. Academic Press, New York, New York. find
  12. Geva, E. 1981 Flowcharting Expository Texts and Reading Comprehension. Paper presented al, Annual Meeting of American Educational Research Association. find
  13. Grosz, B. 1977 The Representation and Use of Focus in Dialogue Understanding. SRI Technical Note No. 151, Menlo Park, California. find
  14. Grosz, B. and Sidner, C. 1986 The Structures of Discourse Structure. Report No. 6097. Bolt, Beranek and Newman (BBN) Cambridge. find
  15. Massachusetts. (also Report No. CSLI-85-39; Attention, Intentions, and the Structure of Discourse, Computational Linguistics 12(3): 175-204. find
  16. Hobbs, J. 1976 A Computational Approach to Discourse Analysis. Rescarch Report No. 76-2. City University of New York Department of Computer, New York, New York. find
  17. Labov, W. and Fanshel, D. 1 9 7 7 Therapeutic Discourse. Academic Press, New York, New York. find
  18. McCarty, L. and Sridharan, N.S. 1981 A Computational Theory of Legal Argumentation. Research Report LRP-TR-13, Rutgers Univcrsity Lab for Computer Science, New Brunswick, New Jersey. find
  19. McGuirc, R., Birnbaum, L. and Flowers, M. 1981 Opportunistic Proc-cssing in Arguments. Proceedings of the International Joint Conference on Artificial lntelligence.bf one;(lJCAl) Conference: 58-60. find
  20. Pollack, M. 1986 A Model of Plan Inference that Distinguishes Between the Beliefs of Actors and Observers. Proceedings of the Association for Computational Linguistics (ACL) Conference: 207-214. find
  21. Quirk, R. et. al. 1972 A Grammar of Contemporary English. Longmans Co., London, England. find
  22. Reichman, R. 1981 Plain Speaking: A Theory and Grammar of Spontaneous Discourse. Report No. 4681, Bolt, Beranek and Newman (BBN), Cambridge, Massachusetts.. find
  23. Sadock, J. 1977 Modus Brevis: The Truncated Argument. Papers from the 13th Regional Meeting, Chicago Linguistics Society: 545-554. find
  24. Sidner, C. 1 9 7 9 Towards a Computational Theory of Definite Anaphora Comprehension in English Discourse. AI Lab Report TR-537, Massacusetts Institute of Technology (MIT), Cambridge, Massachusetts. find
  25. Smedley, T. 1986 An Implementation of a Computational Model for the Analysis of Arguments: An Introduction to the First Attempt. Research Report CS-86-26, University of Waterloo Department of Computer Science, Waterloo, Ontario, Canada. find
  26. Weiner, J. 1979 BLAH, A System which Explains Its Reasoning. Technical Report TR 79-14, University of New Hampshire Computer Science Department, Durham, New Hampshire. find

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