  Code-mixed texts are widespread nowadays due to the advent of social media.
Since these texts combine two languages to formulate a sentence, it gives rise
to various research problems related to Natural Language Processing. In this
paper, we try to excavate one such problem, namely, Parts of Speech tagging of
code-mixed texts. We have built a system that can POS tag English-Bengali
code-mixed data where the Bengali words were written in Roman script. Our
approach initially involves the collection and cleaning of English-Bengali
code-mixed tweets. These tweets were used as a development dataset for building
our system. The proposed system is a modular approach that starts by tagging
individual tokens with their respective languages and then passes them to
different POS taggers, designed for different languages (English and Bengali,
in our case). Tags given by the two systems are later joined together and the
final result is then mapped to a universal POS tag set. Our system was checked
using 100 manually POS tagged code-mixed sentences and it returned an accuracy
of 75.29%
