JTAGGER

Part-of-speech tagging, also called grammatical tagging, is the process of assigning the
words in a text with their corresponding parts of speech like noun, verb, pronoun, or
other lexical class markers to each word in a sentence. Part-of-speech tagging is an
important step in natural language processing.
Part-of-speech tagging is an ambiguous process because a word can represent morethan
one part of speech at different times. Most difficult task is because it deals with
ambiguities of the word. A word, phrase, or sentence is ambiguous if it has more than
one meaning. The word 'light', for example, can mean not very heavy or not very dark.
There are two types of ambiguity which are lexical and structural. When a word has
more than one meaning, it is said to be lexically ambiguous. When a phrase or sentence
can have more than one structure it is said to be structurally ambiguous.
The part-of-speech tagging algorithms fall into three classes which are rule-based
taggers, stochastic taggers, and transformation-based taggers. In this project, rule-based
tagging algorithm is used as the mechanism to develop the system which named
JTagger. The tagger initially tags by assigning each word its most likely tag, estimated
by examining a corpus that consists of Penn Treebank Tagsets.
JTagger is automatically performed the tagging process giving reasonable accuracy thus
eliminate the difficulties of hand tagging task for the reader to manually tag a sentence.
Part-of-speech tagging is important since it could help people to understand English
better.
The programming language used in this system is Java because it is an independent
source that can run in any platform including Microsoft or UNIX.