metadata/README.md

Business Entity Resolution Dataset - Embedding Friendly Scenario

Scenario: data-splink

This synthetic dataset is designed for Vietnamese text-based Entity Resolution / Record Linkage research. It intentionally weakens exact identifiers and creates cross-source textual variation so that language embeddings can contribute beyond traditional fuzzy matching.

Design choices

• High tax_code missing/noisy rate.
• Cross-source schema mismatch.
• Vietnamese text variants: missing diacritics, token merge, token order swap, legal type abbreviation, English translation, short-name-only variants.
• Hard negatives: similar names, same address, same representative, same short name across different true entities.

Important files

• canonical/canonical_business_entity.csv: synthetic clean entity layer.
• observed/*.csv: raw source tables with different schemas.
• evaluation/ground_truth_entity_map.csv: record-to-entity ground truth.
• evaluation/evaluation_labels.csv: pair-level labels for model evaluation.
• metadata/dataset_summary.json: quality summary.

This notebook exports raw source tables only. It does not create a linkage view in advance. The linkage view should be created later inside the matching pipeline notebook.