Rust crate for entity parsing
-
Updated
Dec 26, 2022 - Rust
#
Entity resolution
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.
Here are 7 public repositories matching this topic...
DuckDB community extension for locality-sensitive hashing (LSH)
record-linkage entity-resolution fuzzy-matching lsh locality-sensitive-hashing approximate-nearest-neighbor-search deduplication data-matching duckdb duckdb-extension duckdb-community
-
Updated
Apr 16, 2026 - Rust
Fuzzymatching made easy
-
Updated
May 21, 2024 - Rust
SQL extensions for GoldenMatch — run entity resolution from Postgres (pgrx) and DuckDB (Python UDFs). Rust bridge via pyo3. Part of the Golden Suite.
-
Updated
Mar 27, 2026 - Rust
canon resolves identifiers to canonical forms using versioned registries — normalizing formats, validating checksums, and mapping to canonical IDs deterministically.
-
Updated
Apr 3, 2026 - Rust
Autonomous recursive language-model investigation agent.
agent rust cli osint cqrs entity-resolution knowledge-graph agpl sanctions investigation campaign-finance petgraph llm ratatui corporate-registry
-
Updated
Apr 17, 2026 - Rust
CJK-native master data matching engine — multi-signal phonetic, visual, and normalization matching for Chinese/Japanese/Korean records. Built in Rust, runs in the browser via WASM.
-
Updated
Apr 9, 2026 - Rust
Created by Halbert L. Dunn
Released 1946
- Followers
- 50 followers
- Organization
- entity-resolution
- Website
- github.com/topics/entity-resolution
- Wikipedia
- Wikipedia