---
title: "NER-powered vector search"
sidebarTitle: "NER Search"
description: "Extract named entities and embed them to sharpen retrieval."
---

Uses Named Entity Recognition to power vector search. Extracting entities
(people, places, organizations) and embedding them alongside the text improves
accuracy when queries are about specific things rather than general topics.

<Note>
This example is a runnable notebook in the
[vectordb-recipes](https://github.com/lancedb/vectordb-recipes) repository rather than a page here.
</Note>

<CardGroup cols={2}>
  <Card title="Open in Colab" icon="google" href="https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/tutorials/NER-powered-Semantic-Search/NER_powered_Semantic_Search_with_LanceDB.ipynb">
    Run it end to end in the browser.
  </Card>
  <Card title="View on GitHub" icon="github" href="https://github.com/lancedb/vectordb-recipes/tree/main/tutorials/NER-powered-Semantic-Search">
    Read the source.
  </Card>
</CardGroup>