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Clarify Neural Search ingest pipeline (#4539) 

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>
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kolchfa-aws 2023-08-03 10:18:41 -04:00 committed by GitHub
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_search-plugins/neural-search.md
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@ -19,7 +19,7 @@ The Neural Search plugin comes bundled with OpenSearch. For more information, se
## Ingest data with Neural Search
In order to ingest vectorized documents, you need to create a Neural Search _pipeline_. A pipeline consists of a series of processors that manipulate documents during ingestion, allowing the documents to be vectorized. The following API operation creates a Neural Search pipeline:
In order to ingest vectorized documents, you need to create a Neural Search ingest _pipeline_. An ingest pipeline consists of a series of processors that manipulate documents during ingestion, allowing the documents to be vectorized. The following API operation creates a Neural Search ingest pipeline:
```
PUT _ingest/pipeline/<pipeline_name>
@ -29,7 +29,7 @@ In the pipeline request body, The `text_embedding` processor, the only processor
### Path parameter
Use `pipeline_name` to create a name for your Neural Search pipeline.
Use `pipeline_name` to create a name for your Neural Search ingest pipeline.
### Request fields
@ -78,7 +78,7 @@ In order to use the text embedding processor defined in your pipelines, create a
### Example request
The following example request creates an index that attaches to a Neural Search pipeline. Because the index maps to k-NN vector fields, the index setting field `index-knn` is set to `true`. Furthermore, `mapping` settings use [k-NN method definitions]({{site.url}}{{site.baseurl}}/search-plugins/knn/knn-index/#method-definitions) to match the maps defined in the Neural Search pipeline.
The following example request creates an index that attaches to a Neural Search ingest pipeline. Because the index maps to k-NN vector fields, the index setting field `index-knn` is set to `true`. Furthermore, `mapping` settings use [k-NN method definitions]({{site.url}}{{site.baseurl}}/search-plugins/knn/knn-index/#method-definitions) to match the maps defined in the Neural Search ingest pipeline.
```json
PUT /my-nlp-index-1
@ -130,7 +130,7 @@ POST /my-nlp-index-1/_doc
}
```
With the text_embedding processor in place through a Neural Search pipeline, the example indexes "Hello world" as a `text_field` and converts "Hello world" into an associated k-NN vector field.
With the text_embedding processor in place through a Neural Search ingest pipeline, the example indexes "Hello world" as a `text_field` and converts "Hello world" into an associated k-NN vector field.
## Search a neural index