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--- |
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license: cc-by-4.0 |
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language: |
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- hi |
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- en |
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tags: |
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- code-mixing |
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- Hinglish |
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- expert-annotated |
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size_categories: |
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- 1M<n<10M |
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configs: |
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- config_name: LID |
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data_files: |
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- split: train |
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path: "LID_train.csv" |
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- split: test |
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path: "LID_test.csv" |
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- config_name: MLI |
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data_files: |
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- split: train |
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path: "MLI_train.csv" |
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- split: test |
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path: "MLI_test.csv" |
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- config_name: POS |
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data_files: |
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- split: train |
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path: "POS_train.csv" |
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- split: test |
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path: "POS_test.csv" |
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- config_name: NER |
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data_files: |
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- split: train |
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path: "NER_train.csv" |
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- split: test |
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path: "NER_test.csv" |
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- config_name: MT |
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data_files: |
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- split: train |
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path: "MT_train.csv" |
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- split: test |
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path: "MT_test.csv" |
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--- |
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## Dataset Details |
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**COMI-LINGUA** (**CO**de-**MI**xing and **LING**uistic Insights on Natural Hinglish **U**sage and **A**nnotation) is a high-quality Hindi-English code-mixed dataset, manually annotated by three annotators. It serves as a benchmark for multilingual NLP models by covering multiple foundational tasks. |
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**COMI-LINGUA provides annotations for several key NLP tasks:** |
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* **Language Identification (LID):** Token-wise classification of Hindi, English, and other linguistic units.<br> |
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Initial predictions were generated using the [Microsoft LID tool](https://github.com/microsoft/LID-tool), which annotators then reviewed and corrected. |
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``` |
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Example: |
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sentence: प्रधानमंत्री नरेन्द्र मोदी डिजिटल इंडिया मिशन को आगे बढ़ाने के लिए पिछले सप्ताह Google के CEO सुंदर पिचाई से मुलाकात की थी । |
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LID tags: hi hi hi en en en hi hi hi hi hi hi hi en hi en hi hi hi hi hi hi ot |
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``` |
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* **Matrix Language Identification (MLI):** Sentence-level annotation of the dominant language. |
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``` |
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Example: |
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sentence:"किसानों को अपनी फसल बेचने में दिक्कत न हो इसके लिये Electronic National Agriculture Market यानि ई-नाम योजना तेजी से काम हो रहा है।" Matrix Language: hi |
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sentence:"India’s automation and design expert pool is vast, और ज़्यादातर Global companies के इंजीिनयिंरग center भी भारत में हैं।" Matrix Language: en |
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``` |
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* **Part-of-Speech (POS) Tagging:** Syntactic categorization for linguistic analysis.<br> |
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Tags were pre-assigned using the [CodeSwitch NLP library](https://github.com/sagorbrur/codeswitch), which annotators then reviewed and corrected. |
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``` |
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Example: |
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sentence: भारत द्वारा बनाया गया Unified Payments Interface यानि UPI भारत की एक बहुत बड़ी success story है । |
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POS tags: PROPN ADP VERB VERB PROPN PROPN PROPN CONJ PROPN PROPN ADP DET ADJ ADJ NOUN NOUN VERB X |
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``` |
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* **Named Entity Recognition (NER):** Identification of entities in Hinglish text.<br> |
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Each token is pre-assigned a language tag using the [CodeSwitch NLP library](https://github.com/sagorbrur/codeswitch), which annotators then reviewed and corrected. |
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``` |
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Example: |
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sentence: "मालूम हो कि पेरिस स्थित Financial Action Task Force, FATF ने जून 2018 में पाकिस्तान को ग्रे लिस्ट में रखा था।" |
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NER tags: "पेरिस": GPE, "Financial Action Task Force, FATF": ORGANISATION, "2018": Date, "पाकिस्तान": GPE |
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``` |
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* **Machine Translation (MT):** Parallel translation of sentences in Romanized Hindi and Devanagari Hindi and English languages. |
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Initial translation predictions were generated using the [Llama 3.3 LLM](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct), which annotators then refined and corrected. |
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``` |
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Example: |
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Hinglish Sentence: "भारत में भी green growth, climate resilient infrastructure और ग्रीन transition पर विशेष रूप से बल दिया जा रहा है।" |
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English Translation: "In India too, special emphasis is being given to green growth, climate resilient infrastructure, and green transition." |
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Romanized Hindi Translation: "Bharat mein bhi green growth, climate resilient infrastructure aur green transition par vishesh roop se bal diya ja raha hai." |
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Devnagari Hindi Translation: "भारत में भी हरित विकास, जलवायु सहनशील आधारिक संरचना और हरित संक्रमण पर विशेष रूप से बल दिया जा रहा है।" |
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``` |
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### Dataset Description |
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- **Curated by:** [Lingo Research Group at IIT Gandhinagar](https://lingo.iitgn.ac.in/) |
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- **Funded by:** SERB |
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- **Language(s) (NLP):** Bilingual (Hindi [hi], English [en]) |
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- **Licensed by:** cc-by-4.0 |
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### Dataset Usage Disclaimer ‼️ |
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<span style="color:red">This dataset is a research preview and is subject to ongoing iterative updates. As such, it provides only limited safety measures.</span> |
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## Contact US ✉️ |
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[Lingo Research Group at IIT Gandhinagar, India](https://labs.iitgn.ac.in/lingo/) </br> |
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Mail at: [lingo@iitgn.ac.in](lingo@iitgn.ac.in) |
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## Citation |
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If you use this dataset, please cite the following work: |
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``` |
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@inproceedings{sheth-etal-2025-comi, |
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title = "{COMI}-{LINGUA}: Expert Annotated Large-Scale Dataset for Multitask {NLP} in {H}indi-{E}nglish Code-Mixing", |
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author = "Sheth, Rajvee and |
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Beniwal, Himanshu and |
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Singh, Mayank", |
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editor = "Christodoulopoulos, Christos and |
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Chakraborty, Tanmoy and |
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Rose, Carolyn and |
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Peng, Violet", |
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booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2025", |
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month = nov, |
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year = "2025", |
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address = "Suzhou, China", |
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publisher = "Association for Computational Linguistics", |
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url = "https://aclanthology.org/2025.findings-emnlp.422/", |
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pages = "7973--7992", |
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ISBN = "979-8-89176-335-7", |
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} |
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``` |