Shallow Parsing Pipeline for Hindi-English Code-Mixed Social Media Text
This addresses the problem of text analysis for researchers and practitioners working with Hindi-English code-mixed social media data, though it is incremental as it applies existing methods to a new data type.
The study tackled shallow parsing of Hindi-English code-mixed social media text by developing a pipeline including annotation, language identification, normalization, part-of-speech tagging, and shallow parsing, making it the first such attempt and publicly available.
In this study, the problem of shallow parsing of Hindi-English code-mixed social media text (CSMT) has been addressed. We have annotated the data, developed a language identifier, a normalizer, a part-of-speech tagger and a shallow parser. To the best of our knowledge, we are the first to attempt shallow parsing on CSMT. The pipeline developed has been made available to the research community with the goal of enabling better text analysis of Hindi English CSMT. The pipeline is accessible at http://bit.ly/csmt-parser-api .