source_records/README.md

Source Records

This folder stores supplemental source-side information for the packaged benchmark samples.

Contents

• by_id/<id>.json: one merged JSON record per packaged sample ID.
• html_metadata.json: filtered HTML-derived metadata for packaged sample IDs.
• summary.json: coverage summary for the supplemental export.

Why this exists

The canonical benchmark splits are intentionally task-oriented. They are good for training and evaluation, but some users may want richer provenance fields from the original Glazy pages, such as:

• page title
• author name
• author URL
• long-form description
• page-level status
• HTML-derived UMF and related ratios

The per-sample JSON files expose these fields without forcing users to parse the raw HTML themselves.

Relationship to canonical benchmark files

These files are supplemental. The benchmark-facing train/test splits remain the authoritative interface for evaluation.

Reader script

Use ../tools/read_source_record.py to inspect the packaged source-side data without writing your own loader.

The script supports both quick one-off inspection and small batch exports.

What it can do

• Read one or many sample IDs.
• Read IDs from a text file.
• Return the full merged sample record.
• Return shortcuts such as title, author, description, umf, and raw_html_path.
• Drill into nested fields with a dotted --path lookup.
• Preview the raw HTML directly, with optional tag stripping.
• Export results as json, jsonl, or plain text.
• Save output to a file instead of stdout.

Common examples

Quick summary:

python huggingface/tools/read_source_record.py --summary

List the first 10 packaged sample IDs:

python huggingface/tools/read_source_record.py --list-sample-ids 10

Read the full merged record for one sample:

python huggingface/tools/read_source_record.py --sample-id 100018 --field full

Read a convenience field:

python huggingface/tools/read_source_record.py --sample-id 100018 --field umf
python huggingface/tools/read_source_record.py --sample-id 100018 --field html_metadata
python huggingface/tools/read_source_record.py --sample-id 100018 --field title
python huggingface/tools/read_source_record.py --sample-id 100018 --field raw_html_path

Read a nested path inside the selected field:

python huggingface/tools/read_source_record.py --sample-id 100018 --field full --path property_prediction.test.recipe.umf
python huggingface/tools/read_source_record.py --sample-id 100018 --field full --path html_metadata.title

Preview the raw HTML:

python huggingface/tools/read_source_record.py --sample-id 100018 --html-preview-chars 500
python huggingface/tools/read_source_record.py --sample-id 100018 --html-preview-chars 500 --html-preview-strip-tags

Read multiple samples at once:

python huggingface/tools/read_source_record.py --sample-id 100018 10009 10023 --field title

Read sample IDs from a file:

python huggingface/tools/read_source_record.py --sample-id-file sample_ids.txt --field raw_html_path --output-format jsonl

Export to a file:

python huggingface/tools/read_source_record.py --sample-id 100018 10009 --field full --output-format jsonl --output out/source_records.jsonl

Notes

• --field umf returns the first available UMF found in the merged sample record, preferring split-aligned recipe data and then HTML-derived metadata.
• --path is applied after --field selection, so --field full --path image_generation.train.metadata.image_path works as expected.
• For batch usage, jsonl is usually the easiest format to consume downstream.