david-wb/entity-linking

A bi-encoder model for named entity linking

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Experimental

This project helps developers build systems that can identify and link mentions of entities in text (like names of people, places, or organizations) to a definitive knowledge base. It takes text containing these mentions and outputs the most likely correct entities from a predefined set. This is useful for engineers and data scientists working on natural language processing applications where disambiguating text is critical.

No commits in the last 6 months.

Use this if you are a developer building an entity linking system and need a robust, pre-trained bi-encoder model to map text mentions to known entities, especially for unseen entities.

Not ideal if you are an end-user looking for a ready-to-use application; this is a toolkit for developers to build with.

natural-language-processing information-extraction named-entity-recognition knowledge-graph text-disambiguation
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 8 / 25
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Language

Python

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Last pushed

May 20, 2021

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