README.md

metadata

license: cc-by-4.0
language:
  - hi
  - en
tags:
  - code-mixing
  - Hinglish
  - expert-annotated
size_categories:
  - 1M<n<10M
configs:
  - config_name: LID
    data_files:
      - split: train
        path: LID_train.csv
      - split: test
        path: LID_test.csv
  - config_name: POS
    data_files:
      - split: train
        path: POS_train.csv
      - split: test
        path: POS_test.csv
  - config_name: NER
    data_files:
      - split: train
        path: NER_train.csv
      - split: test
        path: NER_test.csv
  - config_name: Translation
    data_files:
      - split: train
        path: Translation_train.csv
      - split: test
        path: Translation_test.csv

Dataset Details

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 annotators. It serves as a benchmark for multilingual NLP models by covering multiple foundational tasks.

COMI-LINGUA provides annotations for several key NLP tasks:

• 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.
• Matrix Language Identification (MLI): Sentence-level annotation of the dominant language.
• 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.
• Named Entity Recognition (NER): Identification of entities in Hinglish text.
  Each token is pre-assigned a language tag using the CodeSwitch NLP library, which annotators then reviewed and corrected.
• Translation: Parallel translation of sentences in Romanized Hindi and Devanagari Hindi and English languages.
  Initial translation predictions were generated using the Llama 3.3 LLM and refined by human annotators for accuracy.

Dataset Description

• Curated by: Lingo Research Group at IIT Gandhinagar, India
• Funded by: SERB
• Language(s) (NLP): Bilingual (Hindi [hi], English [en])
• License: cc-by-4.0