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Dataset Card for xnli_bn

Dataset Summary

This is a Natural Language Inference (NLI) dataset for Bengali, curated using the subset of MNLI data used in XNLI and state-of-the-art English to Bengali translation model introduced here.

Supported Tasks and Leaderboards

More information needed


  • Bengali


from datasets import load_dataset
dataset = load_dataset("csebuetnlp/xnli_bn")

Dataset Structure

Data Instances

One example from the dataset is given below in JSON format.

  "sentence1": "আসলে, আমি এমনকি এই বিষয়ে চিন্তাও করিনি, কিন্তু আমি এত হতাশ হয়ে পড়েছিলাম যে, শেষ পর্যন্ত আমি আবার তার সঙ্গে কথা বলতে শুরু করেছিলাম",
  "sentence2": "আমি তার সাথে আবার কথা বলিনি।",
  "label": "contradiction"

Data Fields

The data fields are as follows:

  • sentence1: a string feature indicating the premise.
  • sentence2: a string feature indicating the hypothesis.
  • label: a classification label, where possible values are contradiction (0), entailment (1), neutral (2) .

Data Splits

split count
train 381449
validation 2419
test 4895

Dataset Creation

The dataset curation procedure was the same as the XNLI dataset: we translated the MultiNLI training data using the English to Bangla translation model introduced here. Due to the possibility of incursions of error during automatic translation, we used the Language-Agnostic BERT Sentence Embeddings (LaBSE) of the translations and original sentences to compute their similarity. All sentences below a similarity threshold of 0.70 were discarded.

Curation Rationale

More information needed

Source Data


Initial Data Collection and Normalization

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Who are the source language producers?

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More information needed

Annotation process

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Who are the annotators?

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Personal and Sensitive Information

More information needed

Considerations for Using the Data

Social Impact of Dataset

More information needed

Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

More information needed

Licensing Information

Contents of this repository are restricted to only non-commercial research purposes under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0). Copyright of the dataset contents belongs to the original copyright holders.

Citation Information

If you use the dataset, please cite the following paper:

      title={BanglaBERT: Combating Embedding Barrier in Multilingual Models for Low-Resource Language Understanding},
      author={Abhik Bhattacharjee and Tahmid Hasan and Kazi Samin and Md Saiful Islam and M. Sohel Rahman and Anindya Iqbal and Rifat Shahriyar},


Thanks to @abhik1505040 and @Tahmid for adding this dataset.

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