WordNet: a lexical database for English
Communications of the ACM
The descent of hierarchy, and selection in relational semantics
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Investigating the Relations used in Conceptual Combination
Artificial Intelligence Review
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Computational semantics of noun compounds in a semantic space model
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Extracting conceptual feature structures from text
ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
Categorization of malicious behaviors using ontology-based cognitive agents
Data & Knowledge Engineering
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We present an algorithm for automatically disambiguating noun-noun compounds by deducing the correct semantic relation between their constituent words. This algorithm uses a corpus of 2,500 compounds annotated with WordNet senses and covering 139 different semantic relations (we make this corpus available online for researchers interested in the semantics of noun-noun compounds). The algorithm takes as input the WordNet senses for the nouns in a compound, finds all parent senses (hypernyms) of those senses, and searches the corpus for other compounds containing any pair of those senses. The relation with the highest proportional co-occurrence with any sense pair is returned as the correct relation for the compound. This algorithm was tested using a 'leave-one-out' procedure on the corpus of compounds. The algorithm identified the correct relations for compounds with high precision: in 92% of cases where a relation was found with a proportional co-occurrence of 1.0, it was the correct relation for the compound being disambiguated.