Datasets:
TableVerse-5K
A Table-Parsing Benchmark for the StrucTab Framework
GitHub Repo • ModelScope Dataset • Paper
Overview
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.
The benchmark pipeline is illustrated below:
Contents
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:
{
"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 for the full inference and evaluation scripts.
# 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):
TBD
License
This dataset is released for research purposes only.
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