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GoldenMatch

v1.29.0 Feature

This release adds 3 notable features for engineering teams evaluating rollout.

Published 1mo Data Pipelines & ETL
✓ No known CVEs patched
Read the diff → Tool health → What is this tool? →

✓ No known CVEs patched in this version

Topics

data-cleaning data-engineering data-matching data-quality deduplication entity-resolution
+14 more
fellegi-sunter fuzzy-matching knowledge-graph llm master-data-management mcp-server polars pprl python record-linkage rust splink typescript zero-config

Summary

AI summary

Probabilistic auto-config v2 enabled by default with new discriminators and blocking diversification.

Changes in this release

Feature Medium

Improves matching performance across benchmark datasets, beating Splink on pairwise F1.

Improves matching performance across benchmark datasets, beating Splink on pairwise F1.

Source: llm_adapter@2026-06-09

Confidence: low

Feature Low

Enables probabilistic (Fellegi-Sunter) auto-config v2 by default.

Enables probabilistic (Fellegi-Sunter) auto-config v2 by default.

Source: llm_adapter@2026-06-09

Confidence: high

Feature Low

Adds new levers for probabilistic auto-config: dob/date as levenshtein discriminator, drop redundant name composites, diversify blocking on orthogonal keys, admit description/multi_name as token_sort.

Adds new levers for probabilistic auto-config: dob/date as levenshtein discriminator, drop redundant name composites, diversify blocking on orthogonal keys, admit description/multi_name as token_sort.

Source: llm_adapter@2026-06-09

Confidence: high

Feature Low

Wheel and sdist distributions are now cosign-keyless signed with sigstore bundles and build-provenance attestation.

Wheel and sdist distributions are now cosign-keyless signed with sigstore bundles and build-provenance attestation.

Source: llm_adapter@2026-06-09

Confidence: low

Feature Low

Allows disabling the new auto-config via `GOLDENMATCH_FS_AUTOCONFIG_V2=0` to restore legacy behavior.

Allows disabling the new auto-config via `GOLDENMATCH_FS_AUTOCONFIG_V2=0` to restore legacy behavior.

Source: granite4.1:30b@2026-06-09-audit

Confidence: low

Full changelog

goldenmatch 1.29.0

Probabilistic (Fellegi-Sunter) auto-config v2 -- default-on; GOLDENMATCH_FS_AUTOCONFIG_V2=0 restores the legacy field set byte-identically.

Under the shared bench_er_headtohead evaluator (pairwise F1), the probabilistic auto-config path now matches or beats Splink on every measured ER dataset:

| Dataset | goldenmatch v2 | Splink |
|---|---|---|
| historical_50k | 0.779 | 0.757 |
| febrl3 | 0.991 | 0.965 |
| synthetic_person | 0.998 | 0.996 |
| dblp_acm | 0.879 | (skips) |

Levers (probabilistic auto-config path only; the weighted and zero-config dedupe_df paths are untouched): admit dob/date columns as a levenshtein discriminator; drop redundant name composites when atomic given+family exist; additively diversify blocking onto orthogonal stable keys (date-year + postcode/zip); admit description/multi_name as token_sort.

Note: these are pairwise F1 under one shared evaluator; the often-cited ~0.97 Splink figure on historical_50k is a cluster-level metric, not within-cluster pairwise F1.

Wheel and sdist are cosign-keyless signed (sigstore bundles attached) with a build-provenance attestation.

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Related context

Related tools

Earlier breaking changes

  • v3.1.0 `GOLDENMATCH_FRAME=polars` now requires the `[polars]` extra; raises error without it.
  • vgoldencheck-v3.0.0 `inferred_type` emits neutral dtype vocabulary (str/int/uint/float/date/datetime/bool/other) instead of raw Polars dtypes.
  • vgoldencheck-v3.0.0 'inferred_type' now emits a neutral dtype vocabulary instead of raw Polars dtype strings.
  • vgoldencheck-v3.0.0 `scan_file`, `scan_dataframe`, and CLI `check` now run without Polars, using Arrow-native pyarrow.Table.
  • v3.0.0 Result frames now return pyarrow.Table instead of Polars DataFrame.

Beta — feedback welcome: [email protected]