CYC: a large-scale investment in knowledge infrastructure
Communications of the ACM
A maximum-entropy-inspired parser
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
ConceptNet — A Practical Commonsense Reasoning Tool-Kit
BT Technology Journal
Finding predominant word senses in untagged text
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Relieving the data acquisition bottleneck in word sense disambiguation
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Acquiring knowledge from the web to be used as selectors for noun sense disambiguation
CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
SemEval-2007 task 04: classification of semantic relations between nominals
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Common sense reasoning – from cyc to intelligent assistant
Ambient Intelligence in Everyday Life
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In this paper, a framework for acquiring common sense knowledge from the Web is presented. Common sense knowledge includes information about the world that humans use in their everyday lives. To acquire this knowledge, relationships between nouns are retrieved by using search phrases with automatically filled constituents. Through empirical analysis of the acquired nouns over Word-Net, probabilities are produced for relationships between a concept and a word rather than between two words. A specific goal of our acquisition method is to acquire knowledge that can be successfully applied to NLP problems. We test the validity of the acquired knowledge by means of an application to the problem of word sense disambiguation. Results show that the knowledge can be used to improve the accuracy of a state of the art unsupervised disambiguation system.