---
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>