---
license: cc-by-4.0
language:
- hi
- en
tags:
- code-mixing
- text-summarization
size_categories:
- 10K<n<100K
task_categories:
- summarization
configs:
- config_name: Jagran
  data_files:
  - split: train_part1
    path: Jagran/Part1/*.txt
  - split: train_part2
    path: Jagran/Part2/*.txt
  - split: train_part3
    path: Jagran/Part3/*.txt
  - split: train_part4
    path: Jagran/Part4/*.txt
  - split: train_part5
    path: Jagran/Part5/*.txt
- config_name: Aap
  data_files:
  - split: train
    path: aap/*.txt
- config_name: INC
  data_files:
  - split: train
    path: inc/*.txt
- config_name: PIB
  data_files:
  - split: train
    path: pib/*.txt
- config_name: Mankibaat
  data_files:
  - split: train
    path: mankibaat/*.txt
- config_name: PM-speech
  data_files:
  - split: train
    path: pm-speech/*.txt
---

## Dataset Overview 

**MUTANT** (A Multi-sentential Code-mixed Hinglish Dataset): MUTANT is a high-quality Hindi-English code-mixed dataset designed for tasks related to multi-sentential text processing, particularly focusing on summarization and evaluation.

## DATA Sources

MUTANT dataset comprises code-mixed long-length texts extracted from two main sources:

**1. Political Speeches & Press Releases:** Collected from government portals and political party websites.

**2. Hindi News Articles:** Extracted from leading Hindi news websites, ensuring high-quality and formal Hinglish text.

The final dataset contains multiple documents, each of which contains at least one code-mixed MCT. The dataset includes a total of 67007 documents with 84937 MCTs. A significant portion of the documents (44913) belong to the Dainik Jagran dataset.


## Dataset Attribution & Licensing

- **Curated by:** [Lingo Research Group at IIT Gandhinagar](https://lingo.iitgn.ac.in/)
- **Language(s) :** Bilingual (Hindi [hi], English [en])
- **Licensed by:** cc-by-4.0

## Citation

If you use this dataset, please cite the following work:
```
@inproceedings{gupta-etal-2023-mutant,
    title = "{MUTANT}: A Multi-sentential Code-mixed {H}inglish Dataset",
    author = "Gupta, Rahul  and Srivastava, Vivek  and Singh, Mayank",
    editor = "Vlachos, Andreas  and
      Augenstein, Isabelle",
    booktitle = "Findings of the Association for Computational Linguistics: EACL 2023",
    month = may,
    year = "2023",
    address = "Dubrovnik, Croatia",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.findings-eacl.56/",
    doi = "10.18653/v1/2023.findings-eacl.56",
    pages = "744--753"
}
```