WordNet: a lexical database for English
Communications of the ACM
SIGDOC '86 Proceedings of the 5th annual international conference on Systems documentation
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
Expressing implicit semantic relations without supervision
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Automatic identification of semantic relations in Italian complex nominals
IWCS-8 '09 Proceedings of the Eighth International Conference on Computational Semantics
Corpus-Driven hyponym acquisition for turkish language
CICLing'12 Proceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
Extraction of part-whole relations from turkish corpora
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
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Many recent studies have been dedicated to the extraction of semantic connections between words. Using such information at semantic level is likely to improve the performance of Natural Language Processing (NLP) systems, such as text categorization, question answering, information extraction, etc. The scarcity of such resources in Turkish, obstructs new improvements. There are many examples of semantic networks for English and other widely-used languages to lead the way for studies in Turkish. In this study, developing a semantic network for Turkish is aimed by using structural and string patterns in a dictionary. The results are promising, so that approximately two relations can be extracted from 3 definitions. The overall accuracy is 86% if we consider the correct sense assignment, 94% without considering word sense disambiguation.