The rhetorical parsing, summarization, and generation of natural language texts
The rhetorical parsing, summarization, and generation of natural language texts
The rhetorical parsing, summarization, and generation of natural language texts
The rhetorical parsing, summarization, and generation of natural language texts
Automatic detection of causal relations for Question Answering
MultiSumQA '03 Proceedings of the ACL 2003 workshop on Multilingual summarization and question answering - Volume 12
The Proposition Bank: An Annotated Corpus of Semantic Roles
Computational Linguistics
ACM Transactions on Asian Language Information Processing (TALIP)
Extracting Causal Knowledge Using Clue Phrases and Syntactic Patterns
PAKM '08 Proceedings of the 7th International Conference on Practical Aspects of Knowledge Management
Web-Based Knowledge Database Construction Method for Supporting Design
PAKM '08 Proceedings of the 7th International Conference on Practical Aspects of Knowledge Management
Web-based knowledge database construction method for supporting design
Proceedings of the 10th International Conference on Information Integration and Web-based Applications & Services
Latent Variable Models for Causal Knowledge Acquisition
CICLing '07 Proceedings of the 8th International Conference on Computational Linguistics and Intelligent Text Processing
Introduction to Frontiers in Corpus Annotation II: Pie in the Sky
CorpusAnno '05 Proceedings of the Workshop on Frontiers in Corpus Annotations II: Pie in the Sky
Node-first causal network extraction for trend analysis based on web mining
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part II
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We investigated of the characteristics of in-text causal relations. We designed causal relation tags. With our designed tag set, three annotators annotated 750 Japanese newspaper articles. Then, using the annotated corpus, we investigated the causal relation instances from some viewpoints. Our quantitative study shows that what amount of causal relation instances are present, where these relation instances are present, and which types of linguistic expressions are used for expressing these relation instances in text.