license:mit size_categories:n<1K format:csv modality:tabular modality:text library:datasets library:pandas library:mlcroissant library:polars region:us infinite-dataset-hub synthetic
---
license: mit
tags:
- infinite-dataset-hub
- synthetic
---

# LabelingQuest

tags: Data Labeling, NLP, Legal Document Analysis

_Note: This is an AI-generated dataset so its content may be inaccurate or false_

**Dataset Description:**

The 'LabelingQuest' dataset comprises excerpts from legal documents that have been labeled by professionals to indicate whether the document contains a claim. This dataset is valuable for training machine learning models in the context of legal document analysis, specifically focusing on identifying claim statements within legal texts. The labeling is binary, with '1' representing documents containing a claim and '0' representing those without a claim.

**CSV Content Preview:**

```
Title,Text,Label
Case Summary,The defendant failed to adhere to the terms of the contract,1
Amicus Brief,The plaintiff alleges that the defendant breached the contract,1
Court Ruling,The court found no evidence of contractual breach,0
Legal Memorandum,There is a dispute regarding the interpretation of the contract,1
Notice of Appeal,The appellant is challenging the lower court's decision,1
Memorandum Opinion,No claim of breach of contract has been presented,0
```

**Source of the data:**

The dataset was generated using the [Infinite Dataset Hub](https://huggingface.co/spaces/infinite-dataset-hub/infinite-dataset-hub) and microsoft/Phi-3-mini-4k-instruct using the query 'labels as claim or not':

- **Dataset Generation Page**: https://huggingface.co/spaces/infinite-dataset-hub/infinite-dataset-hub?q=labels+as+claim+or+not&dataset=LabelingQuest&tags=Data+Labeling,+NLP,+Legal+Document+Analysis
- **Model**: https://huggingface.co/microsoft/Phi-3-mini-4k-instruct
- **More Datasets**: https://huggingface.co/datasets?other=infinite-dataset-hub
