---
license: other
task_categories: [image-to-text, table-to-text]
language:
- as
- bn
- gu
- hi
- kn
- ml
- or
- pa
- ta
- te
- ur
- zh
- en
tags:
- table
- html
- image-to-html
- table-structure
- structure-only
- SPRINT-MUSTARD
---

# SPRINT-MUSTARD

1429 table image/HTML pairs. **Test split only** -- the source dataset publishes
no train partition, so this is a benchmark, not a training set.

## Ground truth is structure-only -- report TEDS-S, not TEDS

Every `<td>` in the HTML is **empty**. The annotation expresses the grid and the
rowspan/colspan merge relationships and nothing else; the source carries no cell
text.

TEDS compares cell text as well as structure. Against an all-empty ground truth
it degenerates into measuring how well a model reproduces nothing, so **TEDS is
not meaningful on this dataset and only TEDS-S should be reported.**

This is the opposite of TABLET, whose cells do carry values and where TEDS is
the right metric.

## What is in here

`SPRINT-MUSTARD_html_image_pairs.zip` contains a single `test/` directory with
1429 pairs, one `{language}_{n}.png` and one `{language}_{n}.html` each.
The language prefix prevents filename collisions across languages (`hindi_1.png`
vs `tamil_1.png`).

Breakdown: 1215 pairs over 12 Indic languages, plus 214 `scenetext` and the
chinese/english sets already present in the source.

## Files

| file | what |
|---|---|
| `SPRINT-MUSTARD_html_image_pairs.zip` | the 1429 image/HTML pairs (0.56 GB) |
| `SPRINT-MUSTARD_html_image_pairs_说明.txt` | the source dataset's own description, kept verbatim |

## Intended use

Evaluating table **structure** recognition on low-resource scripts, where cell
text transcription is out of scope. Pair it with a text-bearing set such as
TABLET if you need content accuracy.