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Datasets:
hishab
/
openbookqa-bn

Tasks:
Question Answering
Modalities:
Text
Formats:
json
Languages:
Bengali
Size:
1K - 10K
Libraries:
Datasets
pandas
License:
Dataset card Viewer Files Community
1
openbookqa-bn
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---
language:
- bn
license: unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
task_categories:
- question-answering
dataset_info:
- config_name: additional
  features:
  - name: id
    dtype: string
  - name: question_stem
    dtype: string
  - name: choices
    sequence:
    - name: text
      dtype: string
    - name: label
      dtype: string
---

## Data Summary
This is the Bangla-translated version of the [OpenBookQA](https://huggingface.co/datasets/allenai/openbookqa) dataset. The dataset was translated using a new method called Expressive Semantic Translation (EST), which combines Google Machine Translation with LLM-based rewriting modifications. This method enhances the semantic accuracy and expressiveness of the translated content. OpenBookQA focuses on advanced question-answering, requiring multi-step reasoning, additional common and commonsense knowledge, and rich text comprehension, similar to open-book exams.

## Data Details
### Data Instances
### Defaults
An example of a 'train' looks as follows:

```json
{
  "question_stem": "রাতে যখন একটি গাড়ি আপনার কাছে আসছে",
  "choices": {
    "text": ["হেডলাইট আরো তীব্র হয়", "হেডলাইট অন্ধকারে ফিরে যায়", "হেডলাইট একটি ধ্রুবক থাকে", "হেডলাইট বন্ধ"],
    "label": ["A", "B", "C", "D"]
  },
  "answerKey": "A"
}
```

### Data Fields
#### default
The data fields are the same among all splits.

- `id`: a `string` feature.
- `question_stem`: a `string` feature.
- `choices`: a dictionary feature containing:
  - `text`: a `string` feature.
  - `label`: a `string` feature.
- `answerKey`: a `string` feature.

## Data Split
| Split | Number |
| ---- | ----- |
| train | 4947 |
| validation | 500 |
| test | 497 |

## Dataset Creation

### Curation Rationale

### Source Data

#### Initial Data Collection and Normalization

#### Who are the source language producers?

### Annotations

#### Annotation process

#### Who are the annotators?

### Personal and Sensitive Information

## Considerations for Using the Data

### Social Impact of Dataset

### Discussion of Biases

### Other Known Limitations

## Additional Information

### Dataset Curators

### Licensing Information


## Citation Information


## Contributions