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CRF-based Named Entity Recognition @ICON 2013
This paper describes performance of CRF based systems for Named Entity
Recognition (NER) in Indian language as a part of ICON 2013 shared task. In
this task we have considered a set of language independent features for all the
languages. Only for English a language specific feature, i.e. capitalization,
has been added. Next the use of gazetteer is explored for Bengali, Hindi and
English. The gazetteers are built from Wikipedia and other sources. Test
results show that the system achieves the highest F measure of 88% for English
and the lowest F measure of 69% for both Tamil and Telugu. Note that for the
least performing two languages no gazetteer was used. NER in Bengali and Hindi
finds accuracy (F measure) of 87% and 79%, respectively