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_docs/master/ai/metabot.md

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- Whenever you want Metabot to do something completely different, you should reset the conversation, as Metabot might find that irrelevant historical context to be confusing.
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- Once Metabot creates a question for you, you can follow up with more questions or take over yourself. You can drill through the chart or step into the editor to tweak the query (both in the query builder and the SQL editor).
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- Metabot works best with English prompts. While it might understand other languages, you'll get the most reliable results by asking your questions in English.
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- Define domain-specific terms in the [glossary](../exploration-and-organization/data-model-reference#glossary) to help Metabot understand your organization's terminology.
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### Metabot response menu
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_docs/master/ai/settings.md

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- [Add models and metrics to your Metabot collection](#add-models-and-metrics-to-your-metabot-collection)
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- [Add descriptions for your data and content](#add-descriptions-for-your-data-and-content)
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- [Make sure the semantic types for each field are correct](#make-sure-the-semantic-types-for-each-field-are-correct)
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- [Define domain-specific terms in the glossary](#define-domain-specific-terms-in-the-glossary)
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- [Curate prompt suggestions](#curate-prompt-suggestions)
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### Add models and metrics to your Metabot collection
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Metabase will try to set semantic types automatically, but you should confirm that each field has the relevant semantic type. See [Data types and semantic types](../data-modeling/semantic-types). You can also set semantic types for [models](../data-modeling/models#add-metadata-to-columns-in-a-model).
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### Define domain-specific terms in the glossary
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Add your organization's terminology, acronyms, and business-specific terms to the [glossary](../exploration-and-organization/data-model-reference#glossary). When Metabot receives a prompt, it can look up terms in the glossary to better understand your request.
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For example, if you define "MRR" as "Monthly Recurring Revenue" in your glossary, Metabot will know what you mean when you ask "What's our MRR for Q4?" This is especially helpful for industry-specific jargon, internal product names, or abbreviations unique to your organization.
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### Curate prompt suggestions
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When you select a collection for Metabot to "learn", Metabot will suggest a series of prompts based on the content it finds in that collection. These prompts just give people a feel for the kinds of things people can ask Metabot to do.

_docs/master/data-modeling/models.md

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You can edit a model's query by clicking on the down arrow next to the model's name and clicking on **Edit query definition**. When you're doing editing, be sure to save your changes. Unlike questions, which prompt you to save as a new question, any changes here will overwrite the existing model. If you want to create a new model from an existing model, select **Duplicate this model** from the model sidebar (the icon of two overlapping squares).
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### Checking for for breaking changes
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### Checking for breaking changes
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> {% include plans-blockquote.html feature="Checking for breaking changes" %}
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_docs/master/exploration-and-organization/data-model-reference.md

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## Glossary
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The glossary is a place where anyone can define terms relevant to your data. Currently, the glossary is a simple key-value store of terms and their definitions.
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The glossary is a place where anyone can define terms relevant to your data. To add a new term, click **+ New term**. Add the term name and its definitions, then click the checkmark to save the term to the glossary.
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To add a new term, click **+ New term**. Add the term name and its definitions, then click the checkmark to save the term to the glossary.
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The glossary is particularly useful for [Metabot](../ai/metabot). When Metabot gets a prompt, it can look up glossary terms to understand your request. For example, if you define "MRR" as "Monthly Recurring Revenue" in your glossary, Metabot will know what you mean when you ask "What's our MRR for Q4?"
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## Segments
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_docs/master/questions/introduction.md

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Questions saved to a collection can be added to multiple dashboards. Moving a question from one collection to another collection won't have any effect on the dashboards the question has been added to. To save a question to a collection, you'll need to be in a group with [curate access](../permissions/collections#curate-access) to that collection.
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### Checking for for breaking changes
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### Checking for breaking changes
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> {% include plans-blockquote.html feature="Checking for breaking changes" %}
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_site/docs/master/ai/metabot.html

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<li>Whenever you want Metabot to do something completely different, you should reset the conversation, as Metabot might find that irrelevant historical context to be confusing.</li>
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<li>Once Metabot creates a question for you, you can follow up with more questions or take over yourself. You can drill through the chart or step into the editor to tweak the query (both in the query builder and the SQL editor).</li>
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<li>Metabot works best with English prompts. While it might understand other languages, you’ll get the most reliable results by asking your questions in English.</li>
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<li>Define domain-specific terms in the <a href="../exploration-and-organization/data-model-reference#glossary">glossary</a> to help Metabot understand your organization’s terminology.</li>
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</ul>
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<h3 id="metabot-response-menu">Metabot response menu</h3>

_site/docs/master/ai/settings.html

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<li><a href="#add-models-and-metrics-to-your-metabot-collection">Add models and metrics to your Metabot collection</a></li>
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<li><a href="#add-descriptions-for-your-data-and-content">Add descriptions for your data and content</a></li>
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<li><a href="#make-sure-the-semantic-types-for-each-field-are-correct">Make sure the semantic types for each field are correct</a></li>
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<li><a href="#define-domain-specific-terms-in-the-glossary">Define domain-specific terms in the glossary</a></li>
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<li><a href="#curate-prompt-suggestions">Curate prompt suggestions</a></li>
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</ul>
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<p>Metabase will try to set semantic types automatically, but you should confirm that each field has the relevant semantic type. See <a href="../data-modeling/semantic-types">Data types and semantic types</a>. You can also set semantic types for <a href="../data-modeling/models#add-metadata-to-columns-in-a-model">models</a>.</p>
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<h3 id="define-domain-specific-terms-in-the-glossary">Define domain-specific terms in the glossary</h3>
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<p>Add your organization’s terminology, acronyms, and business-specific terms to the <a href="../exploration-and-organization/data-model-reference#glossary">glossary</a>. When Metabot receives a prompt, it can look up terms in the glossary to better understand your request.</p>
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<p>For example, if you define “MRR” as “Monthly Recurring Revenue” in your glossary, Metabot will know what you mean when you ask “What’s our MRR for Q4?” This is especially helpful for industry-specific jargon, internal product names, or abbreviations unique to your organization.</p>
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<h3 id="curate-prompt-suggestions">Curate prompt suggestions</h3>
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<p>When you select a collection for Metabot to “learn”, Metabot will suggest a series of prompts based on the content it finds in that collection. These prompts just give people a feel for the kinds of things people can ask Metabot to do.</p>

_site/docs/master/data-modeling/models.html

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<p>You can edit a model’s query by clicking on the down arrow next to the model’s name and clicking on <strong>Edit query definition</strong>. When you’re doing editing, be sure to save your changes. Unlike questions, which prompt you to save as a new question, any changes here will overwrite the existing model. If you want to create a new model from an existing model, select <strong>Duplicate this model</strong> from the model sidebar (the icon of two overlapping squares).</p>
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<h3 id="checking-for-for-breaking-changes">Checking for for breaking changes</h3>
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<h3 id="checking-for-breaking-changes">Checking for breaking changes</h3>
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<blockquote>
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_site/docs/master/exploration-and-organization/data-model-reference.html

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<h2 id="glossary">Glossary</h2>
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<p>The glossary is a place where anyone can define terms relevant to your data. Currently, the glossary is a simple key-value store of terms and their definitions.</p>
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<p>The glossary is a place where anyone can define terms relevant to your data. To add a new term, click <strong>+ New term</strong>. Add the term name and its definitions, then click the checkmark to save the term to the glossary.</p>
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<p>To add a new term, click <strong>+ New term</strong>. Add the term name and its definitions, then click the checkmark to save the term to the glossary.</p>
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<p>The glossary is particularly useful for <a href="../ai/metabot">Metabot</a>. When Metabot gets a prompt, it can look up glossary terms to understand your request. For example, if you define “MRR” as “Monthly Recurring Revenue” in your glossary, Metabot will know what you mean when you ask “What’s our MRR for Q4?”</p>
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<h2 id="segments">Segments</h2>
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_site/docs/master/questions/introduction.html

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<p>Questions saved to a collection can be added to multiple dashboards. Moving a question from one collection to another collection won’t have any effect on the dashboards the question has been added to. To save a question to a collection, you’ll need to be in a group with <a href="../permissions/collections#curate-access">curate access</a> to that collection.</p>
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<h3 id="checking-for-for-breaking-changes">Checking for for breaking changes</h3>
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<h3 id="checking-for-breaking-changes">Checking for breaking changes</h3>
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<blockquote>
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