  A tagger is a mandatory segment of most text scrutiny systems, as it
consigned a s yntax 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.
