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.gitignore

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README.md

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+---
+license: other
+license_name: research-only
+license_link: LICENSE
+task_categories:
+  - image-to-text
+language:
+  - zh
+  - en
+tags:
+  - Table-Parsing
+  - Table-Recognition
+  - OCR
+pretty_name: TableVerse-5K
+size_categories:
+  - 1K<n<10K
+---
+
+# TableVerse-5K <!-- omit in toc -->
+
+**A Table-Parsing Benchmark for the StrucTab Framework**
+
+<p align="center">
+  <a href="https://github.com/VirtualLUOUCAS/StrucTab">GitHub Repo</a> •
+  <a href="https://modelscope.cn/datasets/pspdada/TableVerse-5K">ModelScope Dataset</a>
+</p>
+
+## Overview <!-- omit in toc -->
+
+**TableVerse-5K** is the evaluation benchmark for **StrucTab**, a structured optimization framework for **table parsing**, the task of converting a table image into structured HTML. Each sample pairs a table image with an instruction prompt and a ground-truth HTML table, and models are scored with the TEDS / TEDS-S metrics.
+
+## Contents <!-- omit in toc -->
+
+- [Statistics](#statistics)
+- [Dataset Structure](#dataset-structure)
+- [Data Format](#data-format)
+- [Usage](#usage)
+- [Citation](#citation)
+- [License](#license)
+
+## Statistics
+
+| Item            | Details                                       |
+| --------------- | --------------------------------------------- |
+| Samples         | 5K table images                               |
+| Task            | Table parsing (image → HTML table)            |
+| Languages       | Bilingual (Chinese and English table content) |
+| Output format   | HTML (`<table>...</table>`)                   |
+| Scoring metrics | TEDS, TEDS-S                                  |
+
+## Dataset Structure
+
+```
+data/
+├── TableVerse_5K.jsonl     # annotations for all samples
+└── images/                 # table images (*.jpg)
+```
+
+## Data Format
+
+Each line of `TableVerse_5K.jsonl` is a JSON object:
+
+```json
+{
+  "image_path": "images/xxx.jpg",
+  "question": "You are an AI specialized in recognizing and extracting table from images...",
+  "ref_answer": "<table>...</table>"
+}
+```
+
+| Field        | Type   | Description                                                       |
+| ------------ | ------ | ----------------------------------------------------------------- |
+| `image_path` | string | Relative path from `data/`; also serves as the unique sample key  |
+| `question`   | string | The instruction / prompt fed to the model together with the image |
+| `ref_answer` | string | Ground-truth table in HTML (`<table>...</table>`)                 |
+
+## Usage
+
+Please refer to the [GitHub repository](https://github.com/VirtualLUOUCAS/StrucTab) for
+the full inference and evaluation scripts.
+
+```bash
+# 1. Clone the code repository
+git clone https://github.com/VirtualLUOUCAS/StrucTab
+cd StrucTab/benchmark
+pip install -r requirements.txt
+
+# 2. Clone this dataset and place its contents under benchmark/data/
+#    so that you have benchmark/data/TableVerse_5K.jsonl and benchmark/data/images/
+
+# 3. Inference
+python infer.py --api_type openai_compat --model_name <model> --base_url <url>
+
+# 4. Score (requires the TEDS judging service, see the repo README)
+python judge.py
+```
+
+## Citation
+
+If you find TableVerse-5K useful, please consider citing (placeholder; to be updated):
+
+```bibtex
+TBD
+```
+
+## License
+
+This dataset is released for **research purposes only**.