Entity resolution topic
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.
conciliator
OpenRefine reconciliation services for VIAF, ORCID, and Open Library + framework for creating more.
learned-string-alignments
Learning String Alignments for Entity Aliases
stance
Learned string similarity for entity names using optimal transport.
nominally
A maximum-strength name parser for record linkage.
kiez
🏘️ Hubness reduced nearest neighbor search for entity alignment with knowledge graph embeddings
Merge-Machine
Merge Dirty Data with Clean Reference Tables
whatis
WhatIs.this: simple entity resolution through Wikipedia
snips-nlu-parsers
Rust crate for entity parsing
spark-matcher
Record matching and entity resolution at scale in Spark
awesome
Curated list of awesome software and resources for Senzing, The First Real-Time AI for Entity Resolution.