An automatic method for generating sense tagged corpora
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Natural Language Engineering
HLT '91 Proceedings of the workshop on Speech and Natural Language
HLT '93 Proceedings of the workshop on Human Language Technology
Building a sense tagged corpus with open mind word expert
WSD '02 Proceedings of the ACL-02 workshop on Word sense disambiguation: recent successes and future directions - Volume 8
Word Sense Disambiguation of Farsi Homographs Using Thesaurus and Corpus
GoTAL '08 Proceedings of the 6th international conference on Advances in Natural Language Processing
NAACL-Demonstrations '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Demonstration Session
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IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Extracting sense-disambiguated example sentences from parallel corpora
WDE '09 Proceedings of the 1st Workshop on Definition Extraction
Cross-lingual word sense disambiguation for languages with scarce resources
Canadian AI'11 Proceedings of the 24th Canadian conference on Advances in artificial intelligence
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CICLing'05 Proceedings of the 6th international conference on Computational Linguistics and Intelligent Text Processing
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Sense tagged corpora play a crucial role in Natural Language Processing, particularly in Word Sense Disambiguation and Natural Language Understanding. Since semantic annotations are usually performed by humans, such corpora are limited to a handful of tagged texts and are not available for many languages with scarce resources including Persian. The shortage of efficient, reliable linguistic resources and fundamental text processing modules for Persian have been a challenge for researchers investigating this language. We employ a newlyproposed cross-lingual sense disambiguation algorithm to automatically create large sense tagged corpora. The initial evaluation of the tagged corpus indicates promising results.