Automatic learning of discourse relations in Swedish using cue phrases

Summary, in English

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.

• Author: Stefan Karlsson; Pierre Nugues
• Editor: Hrafn Loftsson; Eiríkur Rögnvaldsson; Sigrún Helgadóttir
• Department/s: Department of Computer Science; ELLIIT: the Linköping-Lund initiative on IT and mobile communication; Robotics and Semantic Systems
• Publishing year: 2010
• Language: English
• Pages: 179-184
• Publication/Series: Advances in Natural Language Processing / Lecture Notes in Computer Science,
• Volume: 6233
• Links: http://dx.doi.org/10.1007/978-3-642-14770-8_21
• Document type: Conference paper
• Publisher: Springer
• Topic: Computer Science; Electrical Engineering, Electronic Engineering, Information Engineering
• Conference name: 7th International Conference on NLP, IceTAL 2010
• Conference date: 2010-08-16 - 2010-08-18
• Conference place: Reykjavik, Iceland
• Status: Published
• ISBN/ISSN/Other: ISSN: 1611-3349; ISSN: 0302-9743; ISBN: 978-3-642-14769-2