WordNet: a lexical database for English
Communications of the ACM
Using WordNet to automatically deduce relations between words in noun-noun compounds
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
SemEval-2007 task 04: classification of semantic relations between nominals
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
On the semantics of noun compounds
Computer Speech and Language
Automatic interpretation of noun compounds using wordnet similarity
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
A knowledge-rich approach to identifying semantic relations between nominals
Information Processing and Management: an International Journal
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
Logical Ontology Validation Using an Automatic Theorem Prover
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
| Hi-index | 0.01 |
This paper describes a system for classifying semantic relations among nominals, as in SemEval task 4. This system uses a corpus of 2,500 compounds annotated with WordNet senses and covering 139 different semantic relations. Given a set of nominal pairs for training, as provided in the SemEval task 4 training data, this system constructs for each training pair a set of features made up of relations and WordNet sense pairs which occurred with those nominals in the corpus. A Naive Bayes learning algorithm learns associations between these features and relation membership categories. The identification of relations among nominals in test items takes place on the basis of these associations.