Adds links to the semantic_text page (#136801)

* Adds links to the semantic_text page

* Fixes links

* Update for consistency

Author: kosabogi

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

@@ -648,25 +648,13 @@ PUT test-index
 
 You can query `semantic_text` fields using the following query types:
 
-- Match query: The recommended method for querying `semantic_text` fields. You can use [Query DSL](/reference/query-languages/query-dsl/query-dsl-match-query.md) or [ES|QL](/reference/query-languages/esql/functions-operators/search-functions.md#esql-match) syntax.
-<!--
-Refer to examples of match queries on `semantic_text` fields. 
--->
+- Match query: The recommended method for querying `semantic_text` fields. You can use [Query DSL](/reference/query-languages/query-dsl/query-dsl-match-query.md) or [ES|QL](/reference/query-languages/esql/functions-operators/search-functions.md#esql-match) syntax. To learn how to run match queries on `semantic_text` fields, refer to this [example](https://www.elastic.co/docs/solutions/search/semantic-search/semantic-search-semantic-text#semantic-text-semantic-search).
 
-- [kNN query](/reference/query-languages/query-dsl/query-dsl-knn-query.md): Finds the nearest vectors to a query vector using a similarity metric, mainly for advanced or combined search use cases. 
-<!-- 
-Refer to examples of kNN queries on `semantic_text` fields. 
--->
+- kNN query: Finds the nearest vectors to a query vector using a similarity metric, mainly for advanced or combined search use cases. You can use [Query DSL](/reference/query-languages/query-dsl/query-dsl-knn-query.md#knn-query-with-semantic-text) or {applies_to}`stack: ga 9.2` [ES|QL](/reference/query-languages/esql/functions-operators/dense-vector-functions.md#esql-knn) syntax. To learn how to run knn queries on `semantic_text` fields, refer to this [example](/reference/query-languages/query-dsl/query-dsl-knn-query.md#knn-query-with-semantic-text).
 
-- [Sparse vector query](/reference/query-languages/query-dsl/query-dsl-sparse-vector-query.md): Executes searches using sparse vectors generated by a sparse retrieval model such as [ELSER](docs-content://explore-analyze/machine-learning/nlp/ml-nlp-elser.md).
-<!-- 
-Refer to examples of sparse vector queries on `semantic_text` fields.
--->
+- Sparse vector query: Executes searches using sparse vectors generated by a sparse retrieval model such as [ELSER](docs-content://explore-analyze/machine-learning/nlp/ml-nlp-elser.md). You can use it with [Query DSL](/reference/query-languages/query-dsl/query-dsl-sparse-vector-query.md) syntax. To learn how to run sparse vector queries on `semantic_text` fields, refer to this [example](/reference/query-languages/query-dsl/query-dsl-sparse-vector-query.md#example-query-on-a-semantic_text-field).
 
 - [Semantic query](/reference/query-languages/query-dsl/query-dsl-semantic-query.md): We don't recommend this legacy query type for _new_ projects, because the alternatives in this list enable more flexibility and customization. The `semantic` query remains available to support existing implementations.
-<!-- 
-Refer to examples of semantic queries on `semantic_text` fields.
--->
 
 
 ## Troubleshooting semantic_text fields [troubleshooting-semantic-text-fields]