File size: 4,470 Bytes
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pretty_name: SemTPCH
license: other
tags:
- multimodal
- benchmark
- semantic-query
- vision
- audio
- video
---
# SemTPCH
The **data archive** for **SemTPCH**, a multimodal semantic-query benchmark of 22 analytical queries over four datasets (e-commerce, face, video, audio). Each query mixes traditional relational operators with **semantic operators** (semantic filter / classify / map / join / cluster / rank / aggregate) that require perception (vision, audio, or text understanding).
This repository ships **only the curated benchmark data** (media files + tables). Query definitions, the Palimpzest and Claude-Code runners, and the scorer live in the **code repository** ([SemTPCH](https://github.com/curtis-sun/SemTPCH)).
## Quick start
```bash
# from the root of the SemTPCH code repository
tar --zstd -xf semtpch-data.tar.zst
```
This reconstructs `build/{ecommerce,face,ava,vggsound}/`, which is exactly where the runners and scorer read from:
```
build/
├── ecommerce/ { media/, visible.csv, full.csv }
├── face/ { media/, visible.csv, full.csv }
├── ava/ { media/, visible.csv, full.csv, action_list.csv }
└── vggsound/ { media/, visible.csv, full.csv, modalities/keyframes/ }
```
## What's in each table
- **`visible.csv`** — the input rows the system sees (500 rows per dataset). Contains the visible columns plus the media path.
- **`full.csv`** — same rows plus the **hidden perception columns** (e.g. `gender`, `masterCategory`, `articleType`, `hair_color`, `baseColour`, `action_ids`, `label`). Hidden from the system; used only to build gold answers and score.
- Numeric/order columns (`list_price`, `discount`, `return_flag`, `order_date`, …) are **synthetic**, generated in the style of TPC-H.
## Media
| Dataset | Media | Source |
|---|---|---|
| ecommerce | 500 product images | Myntra Fashion Dataset |
| face | 500 face images | CelebA |
| ava | ~1000 video clips, **10 s** each, cut around the AVA middle-frame timestamp | AVA v2.2 |
| vggsound | ~500 audio/video clips, 10 s each, + **150 keyframes** under `modalities/keyframes/` | VGGSound (YouTube) |
For VGGSound, `visible.csv` has a `keyframe_paths` column pointing into `modalities/keyframes/`; the reference pipeline dispatches each row as **caption → keyframe → video** (keyframes are preferred when available to save cost).
## File integrity
| File | Size | SHA-256 |
|---|---|---|
| `semtpch-data.tar.zst` | 1.31 GiB (1,310,566,400 bytes) | `8b81012a47c811e5ae21c359598bda981fdeea4c0a67d74b0830ab77e5d0c309` |
Verify after download:
```bash
echo "8b81012a47c811e5ae21c359598bda981fdeea4c0a67d74b0830ab77e5d0c309 semtpch-data.tar.zst" | sha256sum -c
zstd -t semtpch-data.tar.zst # integrity check
```
The archive contains **2,661 files**. It does **not** contain: the original (full) source datasets, raw/intermediate videos, sample manifests, download scripts, backups, or any logs — only the curated subset above.
## Licensing & intended use
The media in this archive is **derived from** four third-party datasets. Each imposes its own (research / non-commercial) license, and **redistribution of the original source datasets is not permitted** by their terms. This archive is a small, curated benchmark subset provided solely so that published results on SemTPCH can be reproduced.
| Source | License / terms |
|---|---|
| CelebA | Non-commercial research use only |
| Myntra Fashion Dataset | Kaggle Terms of Service (research/personal use) |
| AVA v2.2 | Research use (see the AVA dataset license) |
| VGGSound | Metadata under CC-BY-4.0; audio originates from YouTube and is **not owned** by the VGGSound authors |
**By downloading you agree to use this data solely for non-commercial academic research and to respect each source dataset's license.** No rights to the underlying media are granted or implied beyond what the original sources allow.
## Provenance notes
- **AVA clips** are 10-second segments aligned to AVA's middle-frame timestamp; multiple person/action annotations at the same `(video_id, timestamp)` are aggregated into a single `action_ids` set.
- **VGGSound** clips were fetched from YouTube via `yt-dlp` and trimmed to 10 s; keyframes were extracted for the perception dispatch above. YouTube availability of the original clips is not guaranteed.
- The synthetic relational columns are generated in the TPC-H tradition and carry no third-party restrictions. |