Attention, intentions, and the structure of discourse
Computational Linguistics
The Theory and Practice of Discourse Parsing and Summarization
The Theory and Practice of Discourse Parsing and Summarization
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Building a discourse-tagged corpus in the framework of Rhetorical Structure Theory
SIGDIAL '01 Proceedings of the Second SIGdial Workshop on Discourse and Dialogue - Volume 16
Acquiring the meaning of discourse markers
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Classifying arguments by scheme
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
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Argumentative discourse contains not only language expressing claims and evidence, but also language used to organize these claims and pieces of evidence. Differentiating between the two may be useful for many applications, such as those that focus on the content (e.g., relation extraction) of arguments and those that focus on the structure of arguments (e.g., automated essay scoring). We propose an automated approach to detecting high-level organizational elements in argumentative discourse that combines a rule-based system and a probabilistic sequence model in a principled manner. We present quantitative results on a dataset of human-annotated persuasive essays, and qualitative analyses of performance on essays and on political debates.