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docs/reference/elasticsearch/mapping-reference/semantic-text.md

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1. Returns the first 5 fragments. Increase this value to retrieve additional fragments.
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### Customizing using ingest pipelines [custom-by-pipelines]
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```{applies_to}
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stack: ga 9.0
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```
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In case you want to customize data indexing, use the
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[`sparse_vector`](/reference/elasticsearch/mapping-reference/sparse-vector.md)
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or [`dense_vector`](/reference/elasticsearch/mapping-reference/dense-vector.md)
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field types and create an ingest pipeline with an
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[{{infer}} processor](/reference/enrich-processor/inference-processor.md) to
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generate the embeddings.
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[This tutorial](docs-content://solutions/search/semantic-search/semantic-search-inference.md)
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walks you through the process. In these cases - when you use `sparse_vector` or
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`dense_vector` field types instead of the `semantic_text` field type to
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customize indexing - using the
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[`semantic_query`](/reference/query-languages/query-dsl/query-dsl-semantic-query.md)
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is not supported for querying the field data.
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## Updates to `semantic_text` fields [update-script]
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For indices containing `semantic_text` fields, updates that use scripts have the

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