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.
A browser user interface for manual labeling of record pairs.
100% client-side entity-based topic clustering tool. ML models run in your browser — extract entities, resolve to Wikidata, visualize as knowledge graph.
JedAI-WebApp is a GUI that facilitates the execution of JedAI. JedAI is an open source, high scalability toolkit that offers out-of-the-box solutions for any data integration task. This web-app is developed using spring-boot and ReactJS.
Real-time, direct-from-official-registry company data via MCP. 30 national registries; unmodified raw fields and raw filing bytes. Tools: search, profile, officers, shareholders, charges, filings, financial documents.
Zero-training POCs measuring where a frozen local embedder earns its keep — one model, four endpoint jobs (log/command anomaly, routing, entity resolution) on real data with pre-registered verdicts.
Created by Halbert L. Dunn
Released 1946