Addressed Acrolinx bugs

Author: HeidiSteen

articles/search/semantic-search-overview.md

@@ -18,7 +18,7 @@ ms.custom: references_regions
 
 Currently in Azure Cognitive Search, "semantic search" is a collection of query-related capabilities that bring semantic relevance and language understanding to textual search results. This article is a high-level introduction to semantic search. The embedded video describes the feature, and the section at the end covers availability and pricing.
 
-Semantic search is a premium feature that's metered by usage. We recommend this article for background, but if you'd rather get started, follow these steps:
+Semantic search is a premium feature that's billed by usage. We recommend this article for background, but if you'd rather get started, follow these steps:
 
 > [!div class="checklist"]
 > * [Check regional and service tier requirements](#availability-and-pricing).
@@ -40,7 +40,7 @@ Although semantic search and vector search are closely aligned, this particular
 |---------|-------------|
 | [Semantic re-ranking](semantic-ranking.md) | Uses the context or semantic meaning of a query to compute a new relevance score over existing results. |
 | [Semantic captions and highlights](semantic-how-to-query-request.md) | Extracts sentences and phrases from a document that best summarize the content, with highlights over key passages for easy scanning. Captions that summarize a result are useful when individual content fields are too dense for the results page. Highlighted text elevates the most relevant terms and phrases so that users can quickly determine why a match was considered relevant. |
-| [Semantic answers](semantic-answers.md) | An optional and additional substructure returned from a semantic query. It provides a direct answer to a query that looks like a question. It requires that a document has text with the characteristics of an answer. |
+| [Semantic answers](semantic-answers.md) | An optional and extra substructure returned from a semantic query. It provides a direct answer to a query that looks like a question. It requires that a document has text with the characteristics of an answer. |
 
 ## How semantic ranking works
 
@@ -64,23 +64,23 @@ Query execution proceeds as usual, with term parsing, analysis, and scans over t
 
 In the preparation step, the document corpus returned from the initial result set is analyzed at the sentence and paragraph level to find passages that summarize each document. In contrast with keyword search, this step uses machine reading and comprehension to evaluate the content. Through this stage of content processing, a semantic query returns [captions](semantic-how-to-query-request.md) and [answers](semantic-answers.md). To formulate them, semantic search uses language representation to extract and highlight key passages that best summarize a result. If the search query is a question - and answers are requested - the response will also include a text passage that best answers the question, as expressed by the search query. 
 
-For both captions and answers, existing text is used in the formulation. The semantic models do not compose new sentences or phrases from the available content, nor does it apply logic to arrive at new conclusions. In short, the system will never return content that doesn't already exist.
+For both captions and answers, existing text is used in the formulation. The semantic models don't compose new sentences or phrases from the available content, nor does it apply logic to arrive at new conclusions. In short, the system will never return content that doesn't already exist.
 
 Results are then re-scored based on the [conceptual similarity](semantic-ranking.md) of query terms.
 
 To use semantic capabilities in queries, you'll need to make small modifications to the [search request](semantic-how-to-query-request.md), but no extra configuration or reindexing is required.
 
 ## Semantic capabilities and limitations
 
-Semantic search is a newer technology so it's important to set expectations about what it can and cannot do. What it can do is improve the quality of search by:
+Semantic search is a newer technology so it's important to set expectations about what it can and can't do. What it can do is improve the quality of search by:
 
 * Promoting matches that are semantically closer to the intent of original query.
 
 * Finding strings in each result that can be used as captions, and potentially answers, that can be rendered on a search results page.
 
-What it can't do is rerun the query over the entire corpus to find semantically relevant results. Semantic search re-ranks the *existing* result set, consisting of the top 50 results as scored by the default ranking algorithm. Furthermore, semantic search cannot create new information or strings. Captions and answers are extracted verbatim from your content so if the results do not include answer-like text, the language models will not produce one.
+What it can't do is rerun the query over the entire corpus to find semantically relevant results. Semantic search re-ranks the *existing* result set, consisting of the top 50 results as scored by the default ranking algorithm. Furthermore, semantic search can't create new information or strings. Captions and answers are extracted verbatim from your content so if the results don't include answer-like text, the language models won't produce one.
 
-Although semantic search is not beneficial in every scenario, certain content can benefit significantly from its capabilities. The language models in semantic search work best on searchable content that is information-rich and structured as prose. A knowledge base, online documentation, or documents that contain descriptive content see the most gains from semantic search capabilities.
+Although semantic search isn't beneficial in every scenario, certain content can benefit significantly from its capabilities. The language models in semantic search work best on searchable content that is information-rich and structured as prose. A knowledge base, online documentation, or documents that contain descriptive content see the most gains from semantic search capabilities.
 
 ## Availability and pricing
 
@@ -91,11 +91,11 @@ Semantic search and spell check are available on services that meet the criteria
 | Semantic search | Standard tier (S1, S2, S3, S3 HD), Storage Optimized tier (L1, L2) | [Region availability](https://azure.microsoft.com/global-infrastructure/services/?products=search)| Required | [Pricing](https://azure.microsoft.com/pricing/details/search/) <sup>1</sup>|
 | Spell check | Basic <sup>2</sup> and above  | All | None | None (free) |
 
-<sup>1</sup> On the pricing page, scroll down to view additional features that are billed separately. At lower query volumes (under 1000 monthly), semantic search is free. To go above that limit, you can opt in to the semantic search standard pricing plan. The pricing page shows you the semantic query billing rate for different currencies and intervals.
+<sup>1</sup> On the pricing page, scroll down to view more features that are billed separately. At lower query volumes (under 1000 monthly), semantic search is free. To go above that limit, you can opt in to the semantic search standard pricing plan. The pricing page shows you the semantic query billing rate for different currencies and intervals.
 
-<sup>2</sup> Due to the provisioning mechanisms and lifespan of shared (free) search services, a small number of services happen to have spell check on the free tier. However, spell check availability on free tier services is not guaranteed and should not be expected.
+<sup>2</sup> Due to the provisioning mechanisms and lifespan of shared (free) search services, a few services happen to have spell check on the free tier. However, spell check availability on free tier services isn't guaranteed and shouldn't be expected.
 
-Charges for semantic search are levied when query requests include "queryType=semantic" and the search string is not empty (for example, "search=pet friendly hotels in New York". If your search string is empty ("search=*"), you won't be charged, even if the queryType is set to "semantic".
+Charges for semantic search are levied when query requests include "queryType=semantic" and the search string isn't empty (for example, "search=pet friendly hotels in New York". If your search string is empty ("search=*"), you won't be charged, even if the queryType is set to "semantic".
 
 ## Enable semantic search
 
@@ -109,7 +109,7 @@ By default, semantic search is disabled on all services. To enable semantic sear
 
 :::image type="content" source="media/semantic-search-overview/semantic-search-billing.png" alt-text="Screenshot of enabling semantic search in the Azure portal" border="true":::
 
-Semantic Search's free plan is capped at 1,000 queries per month. After the first 1,000 queries in the free plan, you'll receive an error message letting you know you've exhausted your quota whenever you issue a semantic query. When this happens, you'll need to upgrade to the standard plan to continue using semantic search.
+Semantic Search's free plan is capped at 1,000 queries per month. After the first 1,000 queries in the free plan, you'll receive an error message letting you know you've exhausted your quota whenever you issue a semantic query. When this happens, you need to upgrade to the standard plan to continue using semantic search.
 
 Alternatively, you can also enable semantic search using the [Create or Update Service API](/rest/api/searchmanagement/2021-04-01-preview/services/create-or-update#searchsemanticsearch) that's described in the next section.