kg-release-diff

name: kg-release-diff description: Produce a standardized semantic-modeling diff report between two KG-Microbe merged-KG releases. Use when comparing KG versions to quantify changes in biolink/METPO categories, predicates, relations, CURIE prefixes, knowledge sources, and predicate × category signatures.

KG-Microbe Release Semantic Diff

Purpose

Compare two merged-KG releases (e.g. data/merged/20260120 vs data/merged/20260422_nometatraits) along the axes that matter for semantic modeling, not just row counts:

1. Schema — which columns appear in nodes/edges in each release
2. Biolink / METPO categories — added, removed, count deltas; flags deprecated biolink categories still in use
3. Predicates — added, removed, count deltas; biolink vs METPO vocabulary shift
4. Relation column — added, removed, count deltas (RO / domain terms)
5. CURIE prefix coverage — on node ids, edge subjects, edge objects
6. Knowledge-source / provided_by distribution — which transforms contribute nodes/edges
7. Predicate × (subject category, object category) signatures — the strongest structural fingerprint of modeling choices

The report is a single Markdown file suitable for PRs, release notes, or hand-off to ontology reviewers.

Usage

# Two release directories under data/merged/
poetry run python .claude/skills/kg-release-diff/kg_release_diff.py \
    --old data/merged/20260120 \
    --new data/merged/20260422_nometatraits \
    --out data/merged/release_diff_20260120_vs_20260422_nometatraits.md

# Or provide explicit TSV paths (either can be gzipped)
poetry run python .claude/skills/kg-release-diff/kg_release_diff.py \
    --old-nodes data/merged/old/merged-kg_nodes.tsv \
    --old-edges data/merged/old/merged-kg_edges.tsv \
    --new-nodes data/merged/new/merged-kg_nodes.tsv \
    --new-edges data/merged/new/merged-kg_edges.tsv \
    --old-label 20260120 \
    --new-label 20260422_nometatraits \
    --out release_diff.md

Flags

When to invoke

• Preparing release notes for a new merged KG
• Validating that a transform change produced the intended modeling shift (e.g. biolink → METPO predicate preservation)
• Auditing deprecated biolink terms across releases
• Diagnosing which knowledge source contributes which edge types

How to report findings

When run interactively, after the script finishes:

1. Read back the Summary table and the top 3–5 rows from each change list
2. Call out any deprecated-biolink categories or unregistered-prefix warnings
3. Surface the predicate vocabulary shift (biolink vs METPO %) as a one-sentence takeaway — this is often the headline
4. Point the user at the full report path

The script emits progress lines to stderr ([scan] old nodes: …) so long runs don't look hung.

Implementation

• kg_release_diff.py — streams both TSVs with csv.DictReader (reads by column name, tolerating column order / count differences).
• Counter-based aggregation keeps memory bounded regardless of file size, except for the node id → category map used for predicate × category signatures (~150 MB for a 2 M-node release; disable with --no-signatures if memory-constrained).
• Deprecated biolink categories are listed in BIOLINK_DEPRECATED_CATEGORIES near the top of the script — update as the Biolink Model evolves.

Output structure

The generated Markdown has exactly these sections:

1. Summary (one numbers table)
2. Schema (columns) — nodes and edges subsections
3. Biolink / METPO category usage — added/removed/delta tables + deprecated list
4. Predicate usage — added/removed/delta tables + biolink-vs-METPO shift table
5. Relation column usage
6. CURIE prefix coverage — node id, subject, object subsections
7. primary_knowledge_source distribution
8. provided_by distribution on nodes
9. Predicate × (subject category, object category) signatures (omitted when --no-signatures)

Each added/removed/delta table is capped at 40 rows with a …and N more footer.