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.
• Matrix Language Identification (MLI): Sentence-level annotation of the dominant language.
• Part-of-Speech (POS) Tagging: Syntactic categorization for linguistic analysis.
• Named Entity Recognition (NER): Identification of entities in Hinglish text.
• Translation: Parallel translation of sentences in Romanized Hindi and Devanagari Hindi and English languages.

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