COMI-LINGUA

About Dataset

COMI-LINGUA (COde-MIxing and LINGuistic Insights on Natural Hinglish Usage and Annotation) is a high-quality Hindi-English code-mixed dataset, manually annotated by three expert annotators. It serves as a multitask benchmark for multilingual NLP models.

COMI-LINGUA provides annotations for several key NLP tasks:

1. Language Identification (LID): Token-wise classification of Hindi, English, and other linguistic units.

Initial predictions were generated using the Microsoft LID tool, which annotators then reviewed and corrected.

• Example sentence: प्रधानमंत्री  नरेन्द्र  मोदी  डिजिटल  इंडिया  मिशन  को  आगे  बढ़ाने  के  लिए  पिछले  सप्ताह  Google  के CEO सुंदर पिचाई  से  मुलाकात  की  थी ।
• 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

2. Matrix Language Identification (MLI): Sentence-level annotation of the dominant language.

• Example 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

3. Part-of-Speech (POS) Tagging: Syntactic categorization for linguistic analysis.

Tags were pre-assigned using the CodeSwitch NLP library, which annotators then reviewed and corrected.

• Example sentence:  भारत  द्वारा  बनाया  गया Unified Payments Interface यानि  UPI  भारत  की  एक   बहुत  बड़ी   success  story  है  ।
• POS tags: PROPN  ADP VERB VERB  PROPN   PROPN  PROPN  CONJ  PROPN  PROPN ADP  DET  ADJ  ADJ  NOUN  NOUN  VERB  X

4. Named Entity Recognition (NER): Identification of named entities in Hinglish text.

Each token is pre-assigned a language tag using the CodeSwitch NLP library, which annotators then reviewed and corrected.

• Example sentence: मालूम हो कि पेरिस स्थित Financial Action Task Force, FATF ने जून 2018 में पाकिस्तान को ग्रे लिस्ट में रखा था।
• NER tags: "पेरिस": GPE, "Financial Action Task Force, FATF": ORGANISATION, "2018": Date, "पाकिस्तान": GPE

5. Machine Translation (MT): Parallel translation of sentences in Romanized Hindi and Devanagari Hindi and English languages.

• Example Sentence: भारत में भी green growth, climate resilient infrastructure और ग्रीन transition पर विशेष रूप से बल दिया जा रहा है।
• English: In India too, special emphasis is being given to green growth, climate resilient infrastructure, and green transition.
• Romanized Hindi: Bharat mein bhi green growth, climate resilient infrastructure aur green transition par vishesh roop se bal diya ja raha hai.
• Devanagari Hindi: भारत में भी हरित विकास, जलवायु सहनशील आधारिक संरचना और हरित संक्रमण पर विशेष रूप से बल दिया जा रहा है।

Citation:

@inproceedings{sheth-etal-2025-comi,
    title = "{COMI}-{LINGUA}: Expert Annotated Large-Scale Dataset for Multitask {NLP} in {H}indi-{E}nglish Code-Mixing",
    author = "Sheth, Rajvee  and
      Beniwal, Himanshu  and
      Singh, Mayank",
    editor = "Christodoulopoulos, Christos  and
      Chakraborty, Tanmoy  and
      Rose, Carolyn  and
      Peng, Violet",
    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2025",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.findings-emnlp.422/",
    pages = "7973--7992",
    ISBN = "979-8-89176-335-7",
}