Merge pull request #213206 from aahill/luis-dep-banner

[BULK] [CogSvcs] Luis deprecation banner

Author: v-dirichards

articles/cognitive-services/LUIS/app-schema-definition.md

@@ -9,6 +9,9 @@ ms.date: 08/22/2020
 
 # App schema definition
 
+[!INCLUDE [deprecation notice](./includes/deprecation-notice.md)]
+
+
 The LUIS app is represented in either the `.json` or `.lu` and includes all intents, entities, example utterances, features, and settings.
 
 ## Format
@@ -141,4 +144,4 @@ When you import and export the app, choose either `.json` or `.lu`.
 
 ## Next steps
 
-* Migrate to the [V3 authoring APIs](luis-migration-authoring-entities.md)
+* Migrate to the [V3 authoring APIs](luis-migration-authoring-entities.md)

articles/cognitive-services/LUIS/choose-natural-language-processing-service.md

@@ -9,8 +9,11 @@ ms.date: 10/20/2020
 
 # Use Cognitive Services with natural language processing (NLP) to enrich chat bot conversations
 
+[!INCLUDE [deprecation notice](./includes/deprecation-notice.md)]
+
+
 [!INCLUDE [QnA and LUIS - concepts](../includes/luis-qnamaker-shared-concept.md)]
 
 ## Next steps
 
-* Learn [enterprise design strategies](luis-concept-enterprise.md)
+* Learn [enterprise design strategies](luis-concept-enterprise.md)

articles/cognitive-services/LUIS/client-libraries-rest-api.md

@@ -15,8 +15,7 @@ zone_pivot_groups: programming-languages-set-luis
 ---
 # Quickstart: Language Understanding (LUIS) client libraries and REST API
 
-> [!NOTE]
-> A newer version of Language Understanding capabilities are now available as part of Azure Cognitive Service for Language. For more information see [Azure Cognitive Service for Language Documentation](../language-service/index.yml). For language understanding capabilities within the Language Service, see [Conversational Language Understanding](../language-service/conversational-language-understanding/overview.md), [Custom Named Entity Recognition](../language-service/custom-named-entity-recognition/overview.md), and [Custom Classification](../language-service/custom-classification/overview.md).
+[!INCLUDE [deprecation notice](./includes/deprecation-notice.md)]
 
 Create and query an Azure LUIS artificial intelligence (AI) app with the LUIS SDK client libraries with this quickstart using C#, Python, or JavaScript. You can also use cURL to send requests using the REST API.
 

articles/cognitive-services/LUIS/concepts/application-design.md

@@ -16,6 +16,9 @@ ms.date: 01/10/2022
 
 # Plan your LUIS app
 
+[!INCLUDE [deprecation notice](../includes/deprecation-notice.md)]
+
+
 A Language Understanding (LUIS) app schema contains [intents](../luis-glossary.md#intent) and [entities](../luis-glossary.md#entity) relevant to your subject [domain](../luis-glossary.md#domain). The intents classify user [utterances](../luis-glossary.md#utterance), and the entities extract data from the user utterances. Intents and entities relevant to your subject domain. The intents classify user utterances.
 
 A LUIS app learns and performs most efficiently when you iteratively develop it. Here's a typical iteration cycle:

articles/cognitive-services/LUIS/concepts/entities.md

@@ -16,6 +16,9 @@ ms.date: 07/19/2022
 
 # Entity types
 
+[!INCLUDE [deprecation notice](../includes/deprecation-notice.md)]
+
+
 An entity is an item or an element that is relevant to the user's intent. Entities define data that can be extracted from the utterance and is essential to complete a user's required action. For example:
 
 
@@ -47,9 +50,9 @@ Matching list entities is both case sensitive and it has to be an exact match. N
 
 | Normalized value | Synonyms |
 |--|--|
-| Small | sm, sml, tiny, smallest |
-| Medium | md, mdm, regular, average, middle |
-| Large | lg, lrg, big |
+| Small | `sm`, `sml`, `tiny`, `smallest` |
+| Medium | `md`, `mdm`, `regular`, `average`, `middle` |
+| Large | `lg`, `lrg`, `big` |
 
 See the [list entities reference article](../reference-entity-list.md) for more information.
 
@@ -59,8 +62,8 @@ A regular expression entity extracts an entity based on a regular expression pat
 
 | Entity | Regular expression | Example |
 |--|--|--|
-| Flight Number | flight [A-Z]{2} [0-9]{4} | flight AS 1234 |
-| Credit Card Number | [0-9]{16} | 5478789865437632 |
+| Flight Number | `flight [A-Z]{2} [0-9]{4}` | `flight AS 1234` |
+| Credit Card Number | `[0-9]{16}` | `5478789865437632` |
 
 See the [regex entities reference article](../reference-entity-regular-expression.md) for more information.
 
@@ -74,7 +77,7 @@ When a prebuilt entity is included in your application, its predictions are incl
 | Prebuilt entity | Example value |
 |--|--|
 | PersonName | James, Bill, Tom |
-| DatetimeV2 | 2019-05-02, May 2nd, 8am on May 2nd 2019 |
+| DatetimeV2 | `2019-05-02`, `May 2nd`, `8am on May 2nd 2019` |
 
 See the [prebuilt entities reference article](../luis-reference-prebuilt-entities.md) for more information.
 
@@ -85,9 +88,9 @@ A pattern.Any entity is a variable-length placeholder used only in a pattern's t
 
 | Example utterance | Pattern | Entity |
 |--|--|--|
-| Can I have a burger please? | Can I have a {meal} [please][?] | burger |
-| Can I have a pizza? | Can I have a {meal} [please][?] | pizza |
-| Where can I find The Great Gatsby? | Where can I find {bookName}? | The Great Gatsby |
+| Can I have a burger please? | `Can I have a {meal} [please][?]` | burger |
+| Can I have a pizza? | `Can I have a {meal} [please][?]` | pizza |
+| Where can I find The Great Gatsby? | `Where can I find {bookName}?` | The Great Gatsby |
 
 See the [Pattern.Any entities reference article](../reference-entity-pattern-any.md) for more information.
 

articles/cognitive-services/LUIS/concepts/intents.md

@@ -14,6 +14,9 @@ ms.date: 07/19/2022
 ---
 # Intents 
 
+[!INCLUDE [deprecation notice](../includes/deprecation-notice.md)]
+
+
 An intent represents a task or action the user wants to perform. It is a purpose or goal expressed in a user's [utterance](utterances.md).
 
 Define a set of intents that corresponds to actions users want to take in your application. For example, a travel app would have several intents:

articles/cognitive-services/LUIS/concepts/patterns-features.md

@@ -15,6 +15,9 @@ ms.date: 07/19/2022
 
 # Patterns in LUIS apps
 
+[!INCLUDE [deprecation notice](../includes/deprecation-notice.md)]
+
+
 Patterns are designed to improve accuracy when multiple utterances are very similar. A pattern allows you to gain more accuracy for an intent without providing several more utterances.
 
 ## Patterns solve low intent confidence

articles/cognitive-services/LUIS/concepts/utterances.md

@@ -11,6 +11,9 @@ ms.date: 07/19/2022
 ---
 # Utterances
 
+[!INCLUDE [deprecation notice](../includes/deprecation-notice.md)]
+
+
 Utterances are inputs from users that your app needs to interpret. To train LUIS to extract intents and entities from these inputs, it's important to capture various different example utterances for each intent. Active learning, or the process of continuing to train on new utterances, is essential to the machine-learning intelligence that LUIS provides.
 
 Collect utterances that you think users will enter. Include utterances, which mean the same thing but are constructed in various ways:

articles/cognitive-services/LUIS/data-collection.md

@@ -9,6 +9,9 @@ ms.date: 05/06/2020
 
 # Data collection for your app
 
+[!INCLUDE [deprecation notice](./includes/deprecation-notice.md)]
+
+
 A Language Understanding (LUIS) app needs data as part of app development.
 
 ## Data used in LUIS

articles/cognitive-services/LUIS/developer-reference-resource.md

@@ -11,6 +11,9 @@ ms.custom: "devx-track-js, devx-track-csharp"
 
 # SDK, REST, and CLI developer resources for Language Understanding (LUIS)
 
+[!INCLUDE [deprecation notice](./includes/deprecation-notice.md)]
+
+
 SDKs, REST APIs, CLI, help you develop Language Understanding (LUIS) apps in your programming language. Manage your Azure resources and LUIS predictions.
 
 ## Azure resource management