CYC: a large-scale investment in knowledge infrastructure
Communications of the ACM
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Extracting and evaluating general world knowledge from the Brown corpus
HLT-NAACL-TEXTMEANING '03 Proceedings of the HLT-NAACL 2003 workshop on Text meaning - Volume 9
Coarse-to-fine n-best parsing and MaxEnt discriminative reranking
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Reranking and self-training for parser adaptation
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Say Anything: A Massively Collaborative Open Domain Story Writing Companion
ICIDS '08 Proceedings of the 1st Joint International Conference on Interactive Digital Storytelling: Interactive Storytelling
Large-scale extraction and use of knowledge from text
Proceedings of the fifth international conference on Knowledge capture
Weblogs as a source for extracting general world knowledge
Proceedings of the fifth international conference on Knowledge capture
Augmenting WordNet for deep understanding of text
STEP '08 Proceedings of the 2008 Conference on Semantics in Text Processing
Semi-supervised cause identification from aviation safety reports
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
Analysis of discourse structure with syntactic dependencies and data-driven shift-reduce parsing
IWPT '09 Proceedings of the 11th International Conference on Parsing Technologies
A compact forest for scalable inference over entailment and paraphrase rules
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
People's Web '09 Proceedings of the 2009 Workshop on The People's Web Meets NLP: Collaboratively Constructed Semantic Resources
Learning to predict from textual data
Journal of Artificial Intelligence Research
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We present a method of extracting open-domain commonsense knowledge by applying discourse parsing to a large corpus of personal stories written by Internet authors. We demonstrate the use of a linear-time, joint syntax/discourse dependency parser for this purpose, and we show how the extracted discourse relations can be used to generate open-domain textual inferences. Our evaluations of the discourse parser and inference models show some success, but also identify a number of interesting directions for future work.