Rule based Part of speech Tagger for Homoeopathy Clinical realm
A tagger is a mandatory segment of most text scrutiny systems, as
it consigned a syntax class (e.g., noun, verb, adjective, and
adverb) to every word in a sentence. In this paper, we present a
simple part of speech tagger for homoeopathy clinical language.
This paper reports about the anticipated part of speech tagger for
homoeopathy clinical language. It exploit standard pattern for
evaluating sentences, untagged clinical corpus of 20085 words is
used, from which we had selected 125 sentences (2322 tokens).
The problem of tagging in natural language processing is to find
a way to tag every word in a text as a meticulous part of speech.
The basic idea is to apply a set of rules on clinical sentences and
on each word, Accuracy is the leading factor in evaluating any
POS tagger so the accuracy of proposed tagger is also conversed.
Keywords: POS tagging, Natural language processing, Grammar rules, Homoeopathic Corpus
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