An English Part of Speech Tagging Method Based on Maximum Entropy

As part of speech is a fundamental step in syntactic parsing and machine translation, this paper proposes an English part of speech tagging method based on maximum entropy, and this issue is very crucial for natural language processing. The proposed part of speech tagging system is made up of two steps, that is, (a) Training process and (b) Tagging process. Maximum Entropy estimation is able to compute Probability Density Function of the random variables, and in this paper, we solve the problem of tagging part of speech for English by tackling an optimization problem using maximum entropy. Using the ISO-639-1 code: EN dataset, a series of experiments are conducted. Finally, experimental results prove that the proposed method is very effective to tag part of speech for English.