Abstract
This paper describes experiments to extract discourse relations holding between two text spans in Swedish. We considered three relation types: cause-explanation-evidence (CEV), contrast, and elaboration and we extracted word pairs eliciting these relations. We determined a list of Swedish cue phrases marking explicitly the relations and we learned the word pairs automatically from a corpus of 60 million words. We evaluated the method by building two-way classifiers and we obtained the results: Contrast vs. Other 67.9%, CEV vs. Other 57.7%, and Elaboration vs. Other 52.2%.
The conclusion is that this technique, possibly with improvements or modifications, seems usable to capture discourse relations in Swedish.
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References
Mann, W.C., Thompson, S.A.: Rhetorical structure theory: A theory of text organization. Technical Report RS-87-190, Information Sciences Institute (1987)
Meijer, B. (ed.): Nordisk familjebok. Uggleupplagan edn. Nordisk familjeboks förlags aktiebolag, Stockholm (1904–1926)
Kurohashi, S., Nagao, M.: Automatic detection of discourse structure by checking surface information in sentences. In: Proceedings of the 15th International Conference on Computational Linguistics, COLING 1994, Kyoto, vol. 2, pp. 1123–1127 (1994)
Corston-Oliver, S.: Computing Representations of the Structure of Written Discourse. PhD thesis, University of California, Santa Barbara (1998)
Marcu, D., Echihabi, A.: An unsupervised approach to recognizing discourse relations. In: Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics ACL 2002, Philadelphia, pp. 368–375 (2002)
Koehn, P.: Europarl: A parallel corpus for statistical machine translation. In: Proceedings of The Tenth Machine Translation Summit, Phuket, Thailand (2005)
Carlberger, J., Kann, V.: Implementing an efficient part-of-speech tagger. Software Practice and Experience 29, 815–832 (1999)
Manning, C., Schütze, H.: Foundations of Statistical Natural Language Processing. MIT Press, Cambridge (1999)
Blair-Goldensohn, S., McKeown, K.R., Rambow, O.C.: Building and refining rhetorical-semantic relation models. In: Proceedings of NAACL HLT 2007, Rochester, NY, pp. 428–435 (2007)
Miller, G.A.: WordNet: A lexical database for English. Communications of the ACM 38, 39–41 (1995)
Fellbaum, C.: WordNet: A Lexical Database for English. MIT Press, Cambridge (1998)
Ruppenhofer, J., Baker, C.F., Fillmore, C.J.: The FrameNet database and software tools. In: Braasch, A., Povlsen, C. (eds.) Proceedings of the Tenth Euralex International Congress, Copenhagen, Denmark, vol. 1, pp. 371–375 (2002)
Ejerhed, E., Källgren, G., Wennstedt, O., Åström, M.: The linguistic annotation system of the Stockholm-Umeå project. Technical report, University of Umeå, Department of General Linguistics (1992)
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Karlsson, S., Nugues, P. (2010). Automatic Learning of Discourse Relations in Swedish Using Cue Phrases. In: Loftsson, H., Rögnvaldsson, E., Helgadóttir, S. (eds) Advances in Natural Language Processing. NLP 2010. Lecture Notes in Computer Science(), vol 6233. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14770-8_21
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DOI: https://doi.org/10.1007/978-3-642-14770-8_21
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