WordNet: a lexical database for English
Communications of the ACM
Foundations of statistical natural language processing
Foundations of statistical natural language processing
Implementing an efficient part-of-speech tagger
Software—Practice & Experience
Computing representations of the structure of written discourse
Computing representations of the structure of written discourse
Automatic detection of discourse structure by checking surface information in sentences
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 2
An unsupervised approach to recognizing discourse relations
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
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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.