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weft-script-lineage — synthetic training data + negative-result evidence
Companion data for the model wallfacers/weft-lineage-extractor-1.5b, a research artifact demonstrating that synthetic-only training induces a memorization leak in small models for ETL table-lineage extraction.
Contents
train.jsonl/heldout.jsonl— 10,000 + 600 synthetic ETL scripts with table-lineage labels (Python/Shell).out-jvm/adds the Scala/Java-augmented variant.reports/— the frozen evaluation evidence:eval-report-v2.md— synthetic held-out (near-perfect, the misleading number).eval-real.md/eval-real-jvm.md— four-way comparison on real GitHub scripts.leak-report.md/leak-report-jvm.md— memorization-leak quantification.leak-curve.md— leak vs. model scale (0.5B/1.5B/3B).paper-negative-result-findings.md— the full write-up.ADJUDICATION.md— the human-gold labeling convention (Convention A) + provenance.
Note on real scripts
The real-evaluation gold (realeval/gold/*.jsonl) contains third-party GitHub script
content and is not included here by default (license/redistribution care). It is uploaded
only when the publisher passes --include-real-gold after license review.
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