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Oct 16, 2025
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Links to Unstructured enrichment explainer videos #765

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10 changes: 10 additions & 0 deletions ui/enriching/image-descriptions.mdx
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title: Image descriptions
---

<iframe
width="560"
height="315"
src="https://www.youtube.com/embed/pMQm9ymM3N8"
title="YouTube video player"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
allowfullscreen
></iframe>

After partitioning, you can have Unstructured generate text-based summaries of detected images.

This summarization is done by using models offered through various model providers.
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10 changes: 10 additions & 0 deletions ui/enriching/ner.mdx
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title: Named entity recognition (NER)
---

<iframe
width="560"
height="315"
src="https://www.youtube.com/embed/ZEMegRGjCR0"
title="YouTube video player"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
allowfullscreen
></iframe>

After partitioning, you can have Unstructured generate a list of recognized entities and their types (such as the names of organizations, products, and people) in the content, through a process known as _named entity recognition_ (NER).
You can also have Unstructured generate a list of relationships between the entities that are recognized.

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10 changes: 10 additions & 0 deletions ui/enriching/overview.mdx
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title: Overview
---

<iframe
width="560"
height="315"
src="https://www.youtube.com/embed/brlxpzIpPt0"
title="YouTube video player"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
allowfullscreen
></iframe>

import EnrichmentImagesTablesHiResOnly from '/snippets/general-shared-text/enrichment-images-tables-hi-res-only.mdx';

_Enriching_ adds enhancments to the processed data that Unstructured produces. These enrichments include:
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10 changes: 10 additions & 0 deletions ui/enriching/table-descriptions.mdx
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title: Table descriptions
---

<iframe
width="560"
height="315"
src="https://www.youtube.com/embed/3UIW5PDck74"
title="YouTube video player"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
allowfullscreen
></iframe>

After partitioning, you can have Unstructured generate text-based summaries of detected tables.

This summarization is done by using models offered through various model providers.
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10 changes: 10 additions & 0 deletions ui/enriching/table-to-html.mdx
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title: Tables to HTML
---

<iframe
width="560"
height="315"
src="https://www.youtube.com/embed/lT2ixyunrvA"
title="YouTube video player"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
allowfullscreen
></iframe>

After partitioning, you can have Unstructured generate representations of each detected table in HTML markup format.

This table-to-HTML output is done by using [GPT-4o](https://openai.com/index/hello-gpt-4o/), provided through OpenAI.
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