links, findings

Author: HeidiSteen

articles/search/search-query-lucene-examples.md

@@ -16,10 +16,10 @@ ms.date: 11/04/2019
 
 When constructing queries for Azure Cognitive Search, you can replace the default [simple query parser](query-simple-syntax.md) with the more expansive [Lucene Query Parser in Azure Cognitive Search](query-lucene-syntax.md) to formulate specialized and advanced query definitions. 
 
-The Lucene parser supports complex query constructs, such as field-scoped queries, fuzzy and prefix wildcard search, proximity search, term boosting, and regular expression search. The additional power comes with additional processing requirements so you should expect a slightly longer execution time. In this article, you can step through examples demonstrating query operations available when using the full syntax.
+The Lucene parser supports complex query constructs, such as field-scoped queries, fuzzy search, infix and suffix wildcard search, proximity search, term boosting, and regular expression search. The additional power comes with additional processing requirements so you should expect a slightly longer execution time. In this article, you can step through examples demonstrating query operations available when using the full syntax.
 
 > [!Note]
-> Many of the specialized query constructions enabled through the full Lucene query syntax are not [text-analyzed](search-lucene-query-architecture.md#stage-2-lexical-analysis), which can be surprising if you expect stemming or lemmatization. Lexical analysis is only performed on complete terms (a term query or phrase query). Query types with incomplete terms (prefix query, wildcard query, regex query, fuzzy query) are added directly to the query tree, bypassing the analysis stage. The only transformation performed on incomplete query terms is lowercasing. 
+> Many of the specialized query constructions enabled through the full Lucene query syntax are not [text-analyzed](search-lucene-query-architecture.md#stage-2-lexical-analysis), which can be surprising if you expect stemming or lemmatization. Lexical analysis is only performed on complete terms (a term query or phrase query). Query types with incomplete terms (prefix query, wildcard query, regex query, fuzzy query) are added directly to the query tree, bypassing the analysis stage. The only transformation performed on partial query terms is lowercasing. 
 >
 
 ## Formulate requests in Postman

articles/search/search-query-partial-matching.md

@@ -18,6 +18,9 @@ Partial and pattern search can be problematic if the index doesn't have terms in
 
 The solution is to invoke an analyzer that preserves a complete string, including spaces and special characters if necessary,  so that you can match on partial terms and patterns. Creating an additional field for an intact string, plus using a content-preserving analyzer, is the basis of the solution.
 
+> [!TIP]
+> Familiar with Postman and REST APIs? [Download the query examples collection](https://github.com/Azure-Samples/azure-search-postman-samples/tree/master/full-syntax-examples) to query partial terms and special characters described in this article.
+
 ## What is partial search in Azure Cognitive Search
 
 In Azure Cognitive Search, partial search and pattern is available in these forms:
@@ -146,7 +149,11 @@ Whether you are evaluating analyzers or moving forward with a specific configura
 
 ### Use built-in analyzers
 
-Built-in or predefined analyzers can be specified by name on an `analyzer` property of a field definition, with no additional configuration required in the index. The following example demonstrates how you would set the `whitespace` analyzer on a field. For more information about available built-in analyzers, see [Predefined analyzers list](https://docs.microsoft.com/azure/search/index-add-custom-analyzers#predefined-analyzers-reference). 
+Built-in or predefined analyzers can be specified by name on an `analyzer` property of a field definition, with no additional configuration required in the index. The following example demonstrates how you would set the `whitespace` analyzer on a field. 
+
+Language analyzers, such as the en.microsoft natural language processor, will preserve hyphens in compound words or strings. If query patterns include dashes, using a language analyzer might be sufficient.
+
+For other scenarios and to learn more about other built-in analyzers, see [Predefined analyzers list](https://docs.microsoft.com/azure/search/index-add-custom-analyzers#predefined-analyzers-reference). 
 
 ```json
     {

articles/search/search-query-simple-examples.md

@@ -15,7 +15,7 @@ ms.date: 11/04/2019
 
 In Azure Cognitive Search, the [simple query syntax](query-simple-syntax.md) invokes the default query parser for executing full text search queries against an index. This parser is fast and handles common scenarios, including full text search, filtered and faceted search, and geo-search. 
 
-In this article, we use examples to illustrate the simple syntax.
+In this article, we use examples to illustrate the simple syntax, populating the `search=` parameter of a [Search Documents](https://docs.microsoft.com/rest/api/searchservice/search-documents) operation.
 
 An alternative query syntax is [Full Lucene](query-lucene-syntax.md), supporting more complex query structures, such as fuzzy and wildcard search, which can take additional time to process. For more information and examples demonstrating full syntax, see [Use the full Lucene syntax](search-query-lucene-examples.md).