size_categories:10K<n<100K format:json modality:text library:datasets library:pandas library:mlcroissant library:polars region:us
---
dataset_name: "Entailment Dataset"
dataset_type: "textual entailment"
format: "JSONLines"
description: |
  This dataset contains pairs of "anchor" sentences and their corresponding "positive" and "negative" interpretations. It is designed to aid in tasks involving textual entailment, such as determining if a positive or negative statement accurately reflects the meaning of the given anchor sentence.
fields:
  - name: "anchor"
    description: "A sentence providing a specific statement or assertion."
  - name: "positive"
    description: "A statement that is a positive entailment or interpretation of the anchor."
  - name: "negative"
    description: "A statement that is a negative entailment or interpretation of the anchor."
---

# Entailment Dataset

## Dataset Overview

This dataset contains pairs of "anchor" sentences and their corresponding "positive" and "negative" interpretations. The purpose of this dataset is to aid in tasks involving textual entailment, such as determining if a positive or negative statement accurately reflects the meaning of the given anchor sentence.

## Dataset Structure

The dataset is structured in JSONLines format. Each entry contains the following fields:

- **anchor**: A sentence providing a specific statement or assertion.
- **positive**: A statement that is a positive entailment or interpretation of the anchor.
- **negative**: A statement that is a negative entailment or interpretation of the anchor.

### Example Entry

```json
{
   "anchor": "It saw the light of day again only in free India.",
   "positive": "The artifact or text in question was accessible again after India gained independence.",
   "negative": "The artifact or text has not been available since India's independence."
}
```

## Purpose and Use Cases

This dataset is designed for evaluating models on the following tasks:

- **Textual Entailment**: Determining if a given positive or negative statement is a valid interpretation of the anchor sentence.
- **Natural Language Inference (NLI)**: Evaluating the ability of models to infer relationships between statements.
- **Sentiment Analysis**: Understanding how different interpretations of a statement affect sentiment.

## Data Collection

The sentences were taken from [agentlans/finewebedu-sentences](https://huggingface.co/datasets/agentlans/finewebedu-sentences) and contains a diverse range of topics and contexts. Each anchor sentence is paired with a positive and negative statement to capture both affirming and contradicting interpretations.

The dataset was generated using few-shot learning with a custom large language model.

## Dataset Details

- **Number of Entries**: 54996
- **Fields**: anchor, positive, negative
- **Format**: JSONLines
- **Language**: English
