DIRT @SBT@discovery of inference rules from text
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Extracting Patterns and Relations from the World Wide Web
WebDB '98 Selected papers from the International Workshop on The World Wide Web and Databases
Kernel methods for relation extraction
The Journal of Machine Learning Research
A novel use of statistical parsing to extract information from text
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Logic form transformation of WordNet and its applicability to question answering
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Learning surface text patterns for a Question Answering system
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Extracting relations from large text collections
Extracting relations from large text collections
Combining linguistic and statistical analysis to extract relations from web documents
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Dependency tree kernels for relation extraction
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Unsupervised learning of semantic relations between concepts of a molecular biology ontology
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
RelExt: a tool for relation extraction from text in ontology extension
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
A hybrid approach for relation extraction aimed at the semantic web
FQAS'06 Proceedings of the 7th international conference on Flexible Query Answering Systems
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ining non-taxonomic relations is an important part of the Semantic Web puzzle. Building on the work of the semantic annotation community, we address the problem of extracting relation instances among annotated entities. In particular, we analyze the problem of verb-based relation instantiation in some detail and present a heuristic domain independent approach, based on verb chunking and entity clustering, which doesn't require parsing. We also address the problem of mapping linguistic tuples to relations from the ontology. A case study conducted within the biography domain demonstrates the validity of our results in contrast to related work, whilst examining the complexity of the extraction task and the feasibility of verb-based extraction in general.