# Shallow Parsing Pipeline for Hindi-English Code-Mixed Social Media Text

arXiv: https://arxiv.org/abs/1604.03136 · HTML: https://mlsanity.com/paper/1604.03136/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Apr 2016.

## Built on by (most cited first, 7 of 7)

- [The Decades Progress on Code-Switching Research in NLP: A Systematic Survey on Trends and Challenges](https://mlsanity.com/paper/2212.09660/) (2022)
- [El Volumen Louder Por Favor: Code-switching in Task-oriented Semantic Parsing](https://mlsanity.com/paper/2101.10524/) (2021)
- [Exploring Methods for Building Dialects-Mandarin Code-Mixing Corpora: A Case Study in Taiwanese Hokkien](https://mlsanity.com/paper/2301.08937/) (2023)
- [CST5: Data Augmentation for Code-Switched Semantic Parsing](https://mlsanity.com/paper/2211.07514/) (2022)
- [CMSAOne@Dravidian-CodeMix-FIRE2020: A Meta Embedding and Transformer model for Code-Mixed Sentiment Analysis on Social Media Text](https://mlsanity.com/paper/2101.09004/) (2021)
- [Taxonomic survey of Hindi Language NLP systems](https://mlsanity.com/paper/2102.00214/) (2021)
- [Cyberbullying Detection in Hinglish Text Using MURIL and Explainable AI](https://mlsanity.com/paper/2506.16066/) (2025)

## Abstract (arXiv)

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 .