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Brendan Clement
198812fd53
The existing docs have 254 findings from our shared Vale rules. Contributors would otherwise inherit these when editing the same lines. Clean up the prose across 80 pages: correct product names and a repeated word, simplify a few phrases, and replace dashes with punctuation that fits each sentence. The pinned Vale scan now reports zero findings, with no suppressions.
24 lines
1006 B
Plaintext
24 lines
1006 B
Plaintext
---
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title: "NER-powered vector search"
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sidebarTitle: "NER Search"
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description: "Extract named entities and embed them to sharpen retrieval."
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---
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Uses Named Entity Recognition to power vector search. Extracting entities
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(people, places, organizations) and embedding them alongside the text improves
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accuracy when queries are about specific things rather than general topics.
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<Note>
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This example is a runnable notebook in the
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[vectordb-recipes](https://github.com/lancedb/vectordb-recipes) repository rather than a page here.
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</Note>
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<CardGroup cols={2}>
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<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">
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Run it end to end in the browser.
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</Card>
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<Card title="View on GitHub" icon="github" href="https://github.com/lancedb/vectordb-recipes/tree/main/tutorials/NER-powered-Semantic-Search">
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Read the source.
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</Card>
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</CardGroup>
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