Automated discourse generation using discourse structure relations
Artificial Intelligence - Special volume on natural language processing
Participating in explanatory dialogues: interpreting and responding to questions in context
Participating in explanatory dialogues: interpreting and responding to questions in context
Dialogue act modeling for automatic tagging and recognition of conversational speech
Computational Linguistics
A plan-based analysis of indirect speech acts
Computational Linguistics
Supertagging: an approach to almost parsing
Computational Linguistics
Computational Linguistics
Use of support vector learning for chunk identification
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Determining Modality and Factuality for Text Entailment
ICSC '07 Proceedings of the International Conference on Semantic Computing
Discourse level opinion interpretation
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
MICA: a probabilistic dependency parser based on tree insertion grammars application note
NAACL-Short '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers
Multiple agents and the heuristic ascription of belief
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 1
Committed belief annotation and tagging
ACL-IJCNLP '09 Proceedings of the Third Linguistic Annotation Workshop
Modality and negation: An introduction to the special issue
Computational Linguistics
Are you sure that this happened? assessing the factuality degree of events in text
Computational Linguistics
Did it happen? the pragmatic complexity of veridicality assessment
Computational Linguistics
Modality and negation in simt use of modality and negation in semantically-informed syntactic mt
Computational Linguistics
Detecting power relations from written dialog
ACL '12 Proceedings of ACL 2012 Student Research Workshop
ExProM '12 Proceedings of the Workshop on Extra-Propositional Aspects of Meaning in Computational Linguistics
Statistical modality tagging from rule-based annotations and crowdsourcing
ExProM '12 Proceedings of the Workshop on Extra-Propositional Aspects of Meaning in Computational Linguistics
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We go beyond simple propositional meaning extraction and present experiments in determining which propositions in text the author believes. We show that deep syntactic parsing helps for this task. Our best feature combination achieves an F-measure of 64%, a relative reduction in F-measure error of 21% over not using syntactic features.