Towards Automatic Acquisition of a Fully Sense Tagged Corpus for Persian

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 newly-proposed cross-lingual sense disambiguation algorithm to automatically create large sense tagged corpora. The initial evaluation of the tagged corpus indicates promising results.