Corpus-based acquisition of relative pronoun disambiguation heuristics
ACL '92 Proceedings of the 30th annual meeting on Association for Computational Linguistics
Induction of Logic Programs Based on psi-Terms
ALT '99 Proceedings of the 10th International Conference on Algorithmic Learning Theory
Unsupervised discovery of scenario-level patterns for Information Extraction
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
Learning semantic-level information extraction rules by type-oriented ILP
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Automatic acquisition of domain knowledge for Information Extraction
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Focusing on scenario recognition in information extraction
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 2
UMass/Hughes: description of the CIRCUS system used for MUC-5
MUC5 '93 Proceedings of the 5th conference on Message understanding
Description of the UMass system as used for MUC-6
MUC6 '95 Proceedings of the 6th conference on Message understanding
UMass/Hughes TIPSTER project on extraction from text
HLT '93 Proceedings of the workshop on Human Language Technology
UMass/Hughes: description of the CIRCUS system used for Tipster text
TIPSTER '93 Proceedings of a workshop on held at Fredericksburg, Virginia: September 19-23, 1993
Adopting ontologies for multisource identity resolution
OBI '08 Proceedings of the first international workshop on Ontology-supported business intelligence
Automatically constructing a dictionary for information extraction tasks
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
Learning semantic grammars with constructive inductive logic programming
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
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The UMass/MUC-4 system is based on a form of sentence analysis known as selective concept extraction. This approach to language processing is distinguished by a minimal reliance on syntactic sentence analysis, along with a minimal dictionary customized to operate in a limited domain. Last year, the UMass/MUC-3 system demonstrated the viability of selective concept extraction, but serious questions were raised about the portability and scalability of the technology, particularly with respect to the creation of domain-dependent and task-dependent dictionaries. We estimated that 9 person/months went into the creation of the dictionary used by UMass/MUC-3, and we were unable to say how much domain-dependent lexicon was still missing. We were nevertheless sure that our dictionary coverage was incomplete.