---
language: en
tags:
- claim-grounding
- natural-language-inference
- reasoning
- classification
- grounding
- hallucination
pretty_name: Grounding Claims Dataset
license: cc-by-nc-4.0
task_categories:
- text-classification
---

The **Grounding Claims Dataset** is a multi-domain dataset for evaluating whether a natural language **claim** is grounded (i.e., supported or entailed) by a **document**. The dataset is organized into four subsets, each requiring different types of reasoning:

- **general** (1500 examples): Broad, everyday reasoning  
- **logical** (1000 examples): Logical consistency and inference  
- **time_and_dates** (100 examples): Temporal reasoning  
- **prices_and_math** (100 examples): Numerical and mathematical reasoning  

Each entry consists of:  
- `doc`: A short context or passage  
- `claim`: A natural language statement to verify against the `doc`  
- `label`: A binary label indicating whether the claim is grounded in the document (`1` for grounded, `0` for ungrounded)  
- `dataset`: The source subset name (e.g., `"general"`)

---

## 📌 Features

| Feature  | Type    | Description                                    |
|----------|---------|------------------------------------------------|
| `doc`    | string  | The document or passage providing the context  |
| `claim`  | string  | A statement to verify against the document     |
| `label`  | string  | grounded or ungrounded                         |
| `dataset`| string  | The domain/subset the instance belongs to      |

---

## 📊 Usage

This dataset can be used to train and evaluate models on factual verification, natural language inference (NLI), and claim grounding tasks across multiple domains.

---

## 🏷️ Labels

- `grounded` — The claim is grounded in the document.  
- `ungrounded` — The claim is ungrounded or contradicted by the document.