# Dataset Card for [Kaggle MNLI]

## Table of Contents
- [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 Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [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)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage: https://www.kaggle.com/c/multinli-matched-open-evaluation **
- **Repository: chrishuber/roberta-retrained-mlni **
- **Paper: Inference Detection in NLP Using the MultiNLI and SNLI Datasets**
- **Leaderboard: 8**
- **Point of Contact: chrish@sfsu.edu**

### Dataset Summary

[These are the datasets posted to Kaggle for an inference detection NLP competition. Moving them here to use with Pytorch.]

### Supported Tasks and Leaderboards

Provides train and validation data for sentence pairs with inference labels.
[https://www.kaggle.com/competitions/multinli-matched-open-evaluation/leaderboard]
[https://www.kaggle.com/competitions/multinli-mismatched-open-evaluation/leaderboard]

### Languages

[JSON, Python]

## Dataset Structure

### Data Instances

[More Information Needed]

### Data Fields

[More Information Needed]

### Data Splits

[More Information Needed]

## Dataset Creation

### Curation Rationale

[Reposted from https://www.kaggle.com/c/multinli-matched-open-evaluation and https://www.kaggle.com/c/multinli-mismatched-open-evaluation]

### Source Data

#### Initial Data Collection and Normalization

[Please see the article at https://arxiv.org/abs/1704.05426 which discusses the creation of the MNLI dataset.]

#### Who are the source language producers?

[Please see the article at https://arxiv.org/abs/1704.05426 which discusses the creation of the MNLI dataset.]

### Annotations

#### Annotation process

[Crowdsourcing using MechanicalTurk.]

#### Who are the annotators?

[MechanicalTurk users.]

### Personal and Sensitive Information

[None.]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[Kaggle]

### Licensing Information

[More Information Needed]

### Citation Information

[https://www.kaggle.com/c/multinli-matched-open-evaluation]
[https://www.kaggle.com/c/multinli-mismatched-open-evaluation]

### Contributions

Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.