Add inner hits support to semantic query

docs/reference/query-dsl/semantic-query.asciidoc

@@ -72,7 +72,10 @@ For example, if you have a document that covers varying topics:
 ------------------------------------------------------------
 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" ]
+  "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:TBD]
@@ -318,7 +321,7 @@ GET my-index/_search
 
 [discrete]
 [[advanced-search]]
-=== Advanced search on `semantic_text` fields
+==== Advanced search on `semantic_text` fields
 
 The `semantic` query uses default settings for searching on `semantic_text` fields for ease of use.
 If you want to fine-tune a search on a `semantic_text` field, you need to know the task type used by the `inference_id` configured in `semantic_text`.
@@ -332,7 +335,7 @@ on a `semantic_text` field, it is not supported to use the `semantic_query` on a
 
 [discrete]
 [[search-sparse-inference]]
-==== Search with `sparse_embedding` inference
+===== Search with `sparse_embedding` inference
 
 When the {infer} endpoint uses a `sparse_embedding` model, you can use a <<query-dsl-sparse-vector-query,`sparse_vector` query>> on a <<semantic-text,`semantic_text`>> field in the following way:
 
@@ -361,7 +364,7 @@ You can customize the `sparse_vector` query to include specific settings, like <
 
 [discrete]
 [[search-text-inferece]]
-==== Search with `text_embedding` inference
+===== Search with `text_embedding` inference
 
 When the {infer} endpoint uses a `text_embedding` model, you can use a <<query-dsl-knn-query,`knn` query>> on a `semantic_text` field in the following way: