Co-occurrence Retrieval: A Flexible Framework for Lexical Distributional Similarity
Computational Linguistics
Word Sense Disambiguation: Algorithms and Applications (Text, Speech and Language Technology)
Word Sense Disambiguation: Algorithms and Applications (Text, Speech and Language Technology)
Espresso: leveraging generic patterns for automatically harvesting semantic relations
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Semantic taxonomy induction from heterogenous evidence
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Exploring syntactic features for relation extraction using a convolution tree kernel
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
The WordNet Weaver: Multi-criteria Voting for Semi-automatic Extension of a Wordnet
Canadian AI '09 Proceedings of the 22nd Canadian Conference on Artificial Intelligence: Advances in Artificial Intelligence
Heterogeneous knowledge sources in graph-based expansion of the polish wordnet
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part I
Evaluation method for automated wordnet expansion
SIIS'11 Proceedings of the 2011 international conference on Security and Intelligent Information Systems
Corpus-Based semantic filtering in discovering derivational relations
AIMSA'12 Proceedings of the 15th international conference on Artificial Intelligence: methodology, systems, and applications
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Manual construction of a wordnet can be facilitated by a system that suggests semantic relations acquired from corpora. Such systems tend to produce many wrong suggestions. We propose a method of filtering a raw list of noun pairs potentially linked by hypernymy, and test it on Polish. The method aims for good recall and sufficient precision. The classifiers work with complex features that give clues on the relation between the nouns. We apply a corpus-based measure of semantic relatedness enhanced with a Rank Weight Function. The evaluation is based on the data in Polish WordNet. The results compare favourably with similar methods applied to English, despite the small size of Polish WordNet.