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: MLI
data_files:
- split: train
path: MLI_train.csv
- split: test
path: MLI_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.
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
- 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: Hindi
sentence:"India’s automation and design expert pool is vast, और ज़्यादातर Global companies के इंजीिनयिंरग center भी भारत में हैं।" Matrix Language: English
- 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
- 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.
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
- 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, which annotators then refined and corrected.
Example:
Hinglish Sentence: "भारत में भी green growth, climate resilient infrastructure और ग्रीन transition पर विशेष रूप से बल दिया जा रहा है।"
English Translation: "In India too, special emphasis is being given to green growth, climate resilient infrastructure, and green transition."
Romanized Hindi Translation: "Bharat mein bhi green growth, climate resilient infrastructure aur green transition par vishesh roop se bal diya ja raha hai."
Devnagari Hindi Translation: "भारत में भी हरित विकास, जलवायु सहनशील आधारिक संरचना और हरित संक्रमण पर विशेष रूप से बल दिया जा रहा है।"
Dataset Description
- Curated by: Lingo Research Group at IIT Gandhinagar
- Funded by: SERB
- Language(s) (NLP): Bilingual (Hindi [hi], English [en])
- Licensed by: cc-by-4.0
Dataset Usage Disclaimer ‼️
This dataset is a research preview and is subject to ongoing iterative updates. As such, it provides only limited safety measures and may contain biased or offensive content.
Contact US ✉️
Lingo Research Group at IIT Gandhinagar, India
Mail at: lingo@iitgn.ac.in