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    <title>structured-data</title>
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    <updated>2026-06-15T03:11:19+00:00</updated>
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            <entry>
            <id>https://links.biapy.com/links/198</id>
            <title type="text"><![CDATA[LangExtract]]></title>
            <link rel="alternate" href="https://github.com/google/langextract" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/198"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A Python library for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization. 

LangExtract is a Python library that uses LLMs to extract structured information from unstructured text documents based on user-defined instructions. It processes materials such as clinical notes or reports, identifying and organizing key details while ensuring the extracted data corresponds to the source text.

Related contents:

- [LangExtract - La nouvelle pépite de Google pour extraire des données structurées avec l&amp;#039;IA @ Korben :fr:](https://korben.info/langextract-la-nouvelle-pepite-de-google-pour-extraire-des-donnees-structurees-avec-lia.html).]]>
            </summary>
            <updated>2026-03-14T15:09:02+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4282</id>
            <title type="text"><![CDATA[Schema.org]]></title>
            <link rel="alternate" href="https://schema.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4282"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Schema.org is a collaborative, community activity with a mission to create, maintain, and promote schemas for structured data on the Internet, on web pages, in email messages, and beyond.

Schema.org vocabulary can be used with many different encodings, including RDFa, Microdata and JSON-LD. These vocabularies cover entities, relationships between entities and actions, and can easily be extended through a well-documented extension model. Over 10 million sites use Schema.org to markup their web pages and email messages. Many applications from Google, Microsoft, Pinterest, Yandex and others already use these vocabularies to power rich, extensible experiences.]]>
            </summary>
            <updated>2025-08-29T03:50:19+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4871</id>
            <title type="text"><![CDATA[Protocol Buffers]]></title>
            <link rel="alternate" href="https://protobuf.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4871"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Protocol Buffers are language-neutral, platform-neutral extensible mechanisms for serializing structured data.

- [Protocol Buffers @ GitHub](https://github.com/protocolbuffers/protobuf).

Related contents:

- [Protocol Buffer Design: Principles and Practices for Collaborative Development @ Lyft Engineering&amp;#039;s Medium](https://eng.lyft.com/protocol-buffer-design-principles-and-practices-for-collaborative-development-8f5aa7e6ed85).
- [Better than JSON @ Oya Studio](https://aloisdeniel.com/blog/better-than-json).
- [Binary Formats are Better Than JSON in Browsers!](https://adamfaulkner.github.io/binary_formats_are_better_than_json_in_browsers.html).]]>
            </summary>
            <updated>2025-12-09T07:14:43+00:00</updated>
        </entry>
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