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Revert Semantic Query Passage Ranking Documentation #113982

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Revert Semantic Query Passage Ranking Documentation #113982

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200 changes: 0 additions & 200 deletions docs/reference/query-dsl/semantic-query.asciidoc
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Expand Up @@ -40,209 +40,9 @@ The `semantic_text` field to perform the query on.
(Required, string)
The query text to be searched for on the field.

`inner_hits`::
(Optional, object)
Retrieves the specific passages that match the query.
See <<semantic-query-passage-ranking, passage ranking with the `semantic` query>> for more information.
+
.Properties of `inner_hits`
[%collapsible%open]
====
`from`::
(Optional, integer)
The offset from the first matching passage to fetch.
Used to paginate through the passages.
Defaults to `0`.

`size`::
(Optional, integer)
The maximum number of matching passages to return.
Defaults to `3`.
====

Refer to <<semantic-search-semantic-text,this tutorial>> to learn more about semantic search using `semantic_text` and `semantic` query.

[discrete]
[[semantic-query-passage-ranking]]
==== Passage ranking with the `semantic` query
The `inner_hits` parameter can be used for _passage ranking_, which allows you to determine which passages in the document best match the query.
For example, if you have a document that covers varying topics:

[source,console]
------------------------------------------------------------
POST my-index/_doc/lake_tahoe
{
"inference_field": [
"Lake Tahoe is the largest alpine lake in North America",
"When hiking in the area, please be on alert for bears"
]
}
------------------------------------------------------------
// TEST[skip: Requires inference endpoints]

You can use passage ranking to find the passage that best matches your query:

[source,console]
------------------------------------------------------------
GET my-index/_search
{
"query": {
"semantic": {
"field": "inference_field",
"query": "mountain lake",
"inner_hits": { }
}
}
}
------------------------------------------------------------
// TEST[skip: Requires inference endpoints]

[source,console-result]
------------------------------------------------------------
{
"took": 67,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 1,
"relation": "eq"
},
"max_score": 10.844536,
"hits": [
{
"_index": "my-index",
"_id": "lake_tahoe",
"_score": 10.844536,
"_source": {
...
},
"inner_hits": { <1>
"inference_field": {
"hits": {
"total": {
"value": 2,
"relation": "eq"
},
"max_score": 10.844536,
"hits": [
{
"_index": "my-index",
"_id": "lake_tahoe",
"_nested": {
"field": "inference_field.inference.chunks",
"offset": 0
},
"_score": 10.844536,
"_source": {
"text": "Lake Tahoe is the largest alpine lake in North America"
}
},
{
"_index": "my-index",
"_id": "lake_tahoe",
"_nested": {
"field": "inference_field.inference.chunks",
"offset": 1
},
"_score": 3.2726858,
"_source": {
"text": "When hiking in the area, please be on alert for bears"
}
}
]
}
}
}
}
]
}
}
------------------------------------------------------------
<1> Ranked passages will be returned using the <<inner-hits,`inner_hits` response format>>, with `<inner_hits_name>` set to the `semantic_text` field name.

By default, the top three matching passages will be returned.
You can use the `size` parameter to control the number of passages returned and the `from` parameter to page through the matching passages:

[source,console]
------------------------------------------------------------
GET my-index/_search
{
"query": {
"semantic": {
"field": "inference_field",
"query": "mountain lake",
"inner_hits": {
"from": 1,
"size": 1
}
}
}
}
------------------------------------------------------------
// TEST[skip: Requires inference endpoints]

[source,console-result]
------------------------------------------------------------
{
"took": 42,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 1,
"relation": "eq"
},
"max_score": 10.844536,
"hits": [
{
"_index": "my-index",
"_id": "lake_tahoe",
"_score": 10.844536,
"_source": {
...
},
"inner_hits": {
"inference_field": {
"hits": {
"total": {
"value": 2,
"relation": "eq"
},
"max_score": 10.844536,
"hits": [
{
"_index": "my-index",
"_id": "lake_tahoe",
"_nested": {
"field": "inference_field.inference.chunks",
"offset": 1
},
"_score": 3.2726858,
"_source": {
"text": "When hiking in the area, please be on alert for bears"
}
}
]
}
}
}
}
]
}
}
------------------------------------------------------------

[discrete]
[[hybrid-search-semantic]]
==== Hybrid search with the `semantic` query
Expand Down
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