Abstract:
An efficient and less resource-intensive strategies for Konkani-English code-mixed social media text, which witnesses several challenges as compared to tagging general normal text. Part-of-Speech Tagging is a primary and an important step for many Natural Language Processing Applications is proposed.. This paper reports work on annotating code-mixed Konkani-English data collected from social media site Facebook, which consists of more than four thousands posts from Facebook and developed automatic Part-of-Speech Taggers for this corpus. Part-of-Speech tagging is considered as a classification problem and we use different classifiers such as CRFs, SVM with different combinations of features.
