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# Neural Metrics · Straight at the task: pull the right fields out.
<img src="https://img.shields.io/badge/Neural%20Metrics-document%20extraction-4F46E5?style=for-the-badge" alt="Neural Metrics" />
<img src="https://img.shields.io/badge/fork%20of-nanonets%2Fkey_information_extraction-2563EB?style=flat-square" alt="fork" />
</div>
A key-information-extraction set aimed squarely at the core job - given a document, return the specific values that matter.
**We use it for:** benchmarking field-level precision and recall - measuring how often we hallucinate a plausible-but-absent value.
> ### Attribution
> This is an **unmodified fork** of [`nanonets/key_information_extraction`](https://huggingface.co/datasets/nanonets/key_information_extraction), created by the [Qwen team](https://huggingface.co/Qwen).
> All weights, files and behaviour are identical to upstream — we rehost it so our experiments stay
> reproducible and version-pinned. The original license and all credit remain with the Qwen team.
> If you want the canonical dataset, please use [the original](https://huggingface.co/datasets/nanonets/key_information_extraction).
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<details>
<summary><b>Original dataset card from nanonets/key_information_extraction</b> (click to expand)</summary>
---
license: apache-2.0
task_categories:
- question-answering
language:
- en
tags:
- key-information-extraction
- receipts
- document-information-extraction
size_categories:
- n<1K
---
</details>
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