---
annotations_creators:
- machine-generated
language_creators:
- machine-generated
language:
- as
- bn
- gu
- hi
- kn
- ml
- mr
- or
- pa
- ta
- te
license:
- cc0-1.0
multilinguality:
- multilingual
pretty_name: IE-SemParse
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- text2text
task_ids:
- Semantic-Parsing
---

# Dataset Card for "IE-SemParse"

## Table of Contents

- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
  - [Table of Contents](#table-of-contents)
  - [Dataset Description](#dataset-description)
    - [Dataset Summary](#dataset-summary)
    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
    - [Languages](#languages)
  - [Dataset Structure](#dataset-structure)
    - [Data Instances](#data-instances)
    - [Data Fields](#data-fields)
    - [Data Splits](#data-splits)
  - [Dataset usage](#dataset-usage)
  - [Dataset Creation](#dataset-creation)
    - [Curation Rationale](#curation-rationale)
    - [Source Data](#source-data)
      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
      - [Who are the source language producers?](#who-are-the-source-language-producers)
      - [Human Verification Process](#human-verification-process)
  - [Considerations for Using the Data](#considerations-for-using-the-data)
    - [Social Impact of Dataset](#social-impact-of-dataset)
    - [Discussion of Biases](#discussion-of-biases)
    - [Other Known Limitations](#other-known-limitations)
    - [Dataset Curators](#dataset-curators)
    - [Licensing Information](#licensing-information)
    - [Citation Information](#citation-information)

## Dataset Description

- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
- **Paper:** [Evaluating Inter-Bilingual Semantic Parsing for Indian Languages](https://arxiv.org/abs/2304.13005)
- **Point of Contact:** [Divyanshu Aggarwal](mailto:divyanshuggrwl@gmail.com)

### Dataset Summary

IE-SemParse is a eleven major Indic languages that includes
Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
(‘hi’), and Bengali (‘bn’).

### Supported Tasks and Leaderboards

**Tasks:** Natural Language Inference

**Leaderboards:** Currently there is no Leaderboard for this dataset.

### Languages

- `Assamese (as)`
- `Bengali (bn)`
- `Gujarati (gu)`
- `Kannada (kn)`
- `Hindi (hi)`
- `Malayalam (ml)`
- `Marathi (mr)`
- `Oriya (or)`
- `Punjabi (pa)`
- `Tamil (ta)`
- `Telugu (te)`

## Dataset Structure

### Data Instances

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

  ```python
 {'premise': 'अवधारणात्मक रूप से क्रीम स्किमिंग के दो बुनियादी आयाम हैं-उत्पाद और भूगोल।',
 'hypothesis': 'उत्पाद और भूगोल क्रीम स्किमिंग का काम करते हैं।',
 'label': 1 (neutral) }
  ```

### Data Fields

- `premise (string)`: Premise Sentence
- `hypothesis (string)`: Hypothesis Sentence
- `label (integer)`: Integer label `0` if hypothesis `entails` the premise, `2` if hypothesis `negates` the premise and `1` otherwise.

### Data Splits

<!-- Below is the dataset split given for `hi` dataset.

```python
DatasetDict({
    train: Dataset({
        features: ['premise', 'hypothesis', 'label'],
        num_rows: 392702
    })
    test: Dataset({
        features: ['premise', 'hypothesis', 'label'],
        num_rows: 5010
    })
    validation: Dataset({
        features: ['premise', 'hypothesis', 'label'],
        num_rows: 2490
    })
})

``` -->

Language      | ISO 639-1 Code |Train | Dev | Test |
--------------|----------------|-------|-----|------|
Assamese | as | 392,702 | 5,010 | 2,490 |
Bengali | bn | 392,702 | 5,010 | 2,490 |
Gujarati | gu |  392,702 | 5,010 | 2,490 |
Hindi | hi | 392,702 | 5,010 | 2,490 |
Kannada | kn |  392,702 | 5,010 | 2,490 |
Malayalam | ml |392,702  | 5,010 | 2,490 |
Marathi | mr |392,702 | 5,010 | 2,490 |
Oriya | or | 392,702 | 5,010 | 2,490 |
Punjabi | pa | 392,702 | 5,010 | 2,490 |
Tamil | ta | 392,702 | 5,010 | 2,490 |
Telugu | te | 392,702 | 5,010 | 2,490 |

<!-- The dataset split remains same across all languages. -->

## Dataset usage

Code snippet for using the dataset using datasets library.

```python
from datasets import load_dataset

dataset = load_dataset("Divyanshu/indicxnli")
```

## Dataset Creation

Machine translation of XNLI english dataset to 11 listed Indic Languages.

### Curation Rationale

[More information needed]

### Source Data

[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)

#### Initial Data Collection and Normalization

[Detailed in the paper](https://arxiv.org/abs/2304.13005)

#### Who are the source language producers?

[Detailed in the paper](https://arxiv.org/abs/2304.13005)

#### Human Verification Process

[Detailed in the paper](https://arxiv.org/abs/2304.13005)

## Considerations for Using the Data

### Social Impact of Dataset

[Detailed in the paper](https://arxiv.org/abs/2304.13005)

### Discussion of Biases

[Detailed in the paper](https://arxiv.org/abs/2304.13005)

### Other Known Limitations

[Detailed in the paper](https://arxiv.org/abs/2304.13005)

### Dataset Curators

Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan

### Licensing Information

Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.

### Citation Information

If you use any of the datasets, models or code modules, please cite the following paper:

```
@misc{https://doi.org/10.48550/arxiv.2204.08776,
  doi = {10.48550/ARXIV.2204.08776},
  
  url = {https://arxiv.org/abs/2304.13005},
  
  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
  
  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
  
  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
  
  publisher = {arXiv},
  
  year = {2022},
  
  copyright = {Creative Commons Attribution 4.0 International}
}
```

<!-- ### Contributions -->