Induction of semantic classes from natural language text
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Noun-phrase co-occurrence statistics for semiautomatic semantic lexicon construction
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Noun classification from predicate-argument structures
ACL '90 Proceedings of the 28th annual meeting on Association for Computational Linguistics
A bootstrapping method for learning semantic lexicons using extraction pattern contexts
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Weakly supervised named entity transliteration and discovery from multilingual comparable corpora
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Can we derive general world knowledge from texts?
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Class-driven attribute extraction
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Automatic fine-grained semantic classification for domain adaptation
STEP '08 Proceedings of the 2008 Conference on Semantics in Text Processing
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We describe the use of a weakly supervised bootstrapping algorithm in discovering contrasting semantic categories from a source lexicon with little training data. Our method primarily exploits the patterns in sentential contexts where different categories of words may appear. Experimental results are presented showing that such automatically categorized terms tend to agree with human judgements.