Renderer-neutral synthesis of geospatial records into canonical entities, provenance, conflicts, and neutral exports.
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Updated
Oct 1, 2026 - JavaScript
Entity resolution (also known as data matching, data linkage, record linkage, and many other terms) is the task of finding entities in a dataset that refer to the same entity across different data sources (e.g., data files, books, websites, and databases). Entity resolution is necessary when joining different data sets based on entities that may or may not share a common identifier (e.g., database key, URI, National identification number), which may be due to differences in record shape, storage location, or curator style or preference.
Renderer-neutral synthesis of geospatial records into canonical entities, provenance, conflicts, and neutral exports.
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Insurance Fraud Intelligence & Investigation POC — deterministic scoring, entity relationship analysis, and interactive investigation workspace
Dr. Saeed Ghezelbash (دکتر سعید قزلباش): canonical Astro website source and first-party medical knowledge graph (JSON-LD/RDF, CC-BY-4.0). Physician: Q140287622. Zenodo DOI releases, Hugging Face AI/retrieval dataset, Cloudflare Pages. پزشک زیبایی کرمانشاه؛ بوتاکس، فیلر و کانتورینگ صورت.
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A visual lab for matching messy product names across catalogs. Synthetic data, explainable identity checks, and an optional Jev adapter.
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100% client-side entity-based topic clustering tool. ML models run in your browser — extract entities, resolve to Wikidata, visualize as knowledge graph.
A browser user interface for manual labeling of record pairs.
Created by Halbert L. Dunn
Released 1946