Merge pull request #112404 from diberry/diberry/0422-luis-limits

[Cogsvcs] LUIS - rename boundary to limit

Author: GitHubber17

.openpublishing.redirection.json

@@ -727,7 +727,10 @@
       "redirect_url": "/azure/cognitive-services/personalizer/how-to-manage-model",
       "redirect_document_id": false
     },
-
+    {
+      "source_path": "articles/cognitive-services/LUIS/luis-boundaries.md",
+      "redirect_url": "/azure/cognitive-services/LUIS/luis-limits"
+    },
       {
         "source_path": "articles/cognitive-services/LUIS/luis-migration-api-authoring.md",
         "redirect_url": "/azure/cognitive-services/LUIS/luis-migration-authoring-entities",

articles/cognitive-services/LUIS/index.yml

@@ -129,7 +129,7 @@ landingContent:
           - text: Developer resources
             url: developer-reference-resource.md
           - text: App limitations
-            url: luis-boundaries.md
+            url: luis-limits.md
           - text: Prebuilt entities
             url: luis-reference-prebuilt-entities.md
           - text: Custom Entities

articles/cognitive-services/LUIS/luis-concept-data-conversion.md

@@ -16,11 +16,11 @@ ms.author: diberry
 # Convert data format of utterances
 LUIS provides the following conversions of a user utterance before prediction"
 
-* Speech to text using [Cognitive Services Speech](../Speech-Service/overview.md) service. 
+* Speech to text using [Cognitive Services Speech](../Speech-Service/overview.md) service.
 
 ## Speech to text
 
-Speech to text is provided as an integration with LUIS. 
+Speech to text is provided as an integration with LUIS.
 
 ### Intent conversion concepts
 Conversion of speech to text in LUIS allows you to send spoken utterances to an endpoint and receive a LUIS prediction response. The process is an integration of the [Speech](https://docs.microsoft.com/azure/cognitive-services/Speech) service with LUIS. Learn more about Speech to Intent with a [tutorial](../speech-service/how-to-recognize-intents-from-speech-csharp.md).
@@ -29,10 +29,10 @@ Conversion of speech to text in LUIS allows you to send spoken utterances to an
 You do not need to create a **Bing Speech API** key for this integration. A **Language Understanding** key created in the Azure portal works for this integration. Do not use the LUIS starter key.
 
 ### Pricing Tier
-This integration uses a different [pricing](luis-boundaries.md#key-limits) model than the usual Language Understanding pricing tiers. 
+This integration uses a different [pricing](luis-limits.md#key-limits) model than the usual Language Understanding pricing tiers.
 
 ### Quota usage
-See [Key limits](luis-boundaries.md#key-limits) for information. 
+See [Key limits](luis-limits.md#key-limits) for information.
 
 ## Next steps
 

articles/cognitive-services/LUIS/luis-concept-data-extraction.md

@@ -26,7 +26,7 @@ Learn more about the [V3 prediction endpoint](luis-migration-api-v3.md).
 
 * * *
 
-The `appID` is available on the **Settings** page of your LUIS app as well as part of the URL (after `/apps/`) when you're editing that LUIS app. The `subscription-key` is the endpoint key used for querying your app. While you can use your free authoring/starter key while you're learning LUIS, it is important to change the endpoint key to a key that supports your [expected LUIS usage](luis-boundaries.md#key-limits). The `timezoneOffset` unit is minutes.
+The `appID` is available on the **Settings** page of your LUIS app as well as part of the URL (after `/apps/`) when you're editing that LUIS app. The `subscription-key` is the endpoint key used for querying your app. While you can use your free authoring/starter key while you're learning LUIS, it is important to change the endpoint key to a key that supports your [expected LUIS usage](luis-limits.md#key-limits). The `timezoneOffset` unit is minutes.
 
 The **HTTPS response** contains all the intent and entity information LUIS can determine based on the current published model of either the staging or production endpoint. The endpoint URL is found on the [LUIS](luis-reference-regions.md) website, in the **Manage** section, on the **Keys and endpoints** page.
 

articles/cognitive-services/LUIS/luis-concept-intent.md

@@ -18,81 +18,81 @@ An intent represents a task or action the user wants to perform. It is a purpose
 
 Define a set of intents that corresponds to actions users want to take in your application. For example, a travel app defines several intents:
 
-Travel app intents   |   Example utterances   | 
+Travel app intents   |   Example utterances   |
 ------|------|
  BookFlight     |   "Book me a flight to Rio next week" <br/> "Fly me to Rio on the 24th" <br/> "I need a plane ticket next Sunday to Rio de Janeiro"    |
  Greeting     |   "Hi" <br/>"Hello" <br/>"Good morning"  |
  CheckWeather | "What's the weather like in Boston?" <br/> "Show me the forecast for this weekend" |
  None         | "Get me a cookie recipe"<br>"Did the Lakers win?" |
 
-All applications come with the predefined intent, "[None](#none-intent)", which is the fallback intent. 
+All applications come with the predefined intent, "[None](#none-intent)", which is the fallback intent.
 
 ## Prebuilt domains provide intents
-In addition to intents that you define, you can use prebuilt intents from one of the [prebuilt domains](luis-how-to-use-prebuilt-domains.md). 
+In addition to intents that you define, you can use prebuilt intents from one of the [prebuilt domains](luis-how-to-use-prebuilt-domains.md).
 
 ## Return all intents' scores
-You assign an utterance to a single intent. When LUIS receives an utterance on the endpoint, by default, it returns the top intent for that utterance. 
+You assign an utterance to a single intent. When LUIS receives an utterance on the endpoint, by default, it returns the top intent for that utterance.
 
-If you want the scores for all intents for the utterance, you can provide a flag on the query string of the prediction API. 
+If you want the scores for all intents for the utterance, you can provide a flag on the query string of the prediction API.
 
 |Prediction API version|Flag|
 |--|--|
 |V2|`verbose=true`|
 |V3|`show-all-intents=true`|
 
 ## Intent compared to entity
-The intent represents action the application should take for the user and is based on the entire utterance. An utterance can have only one top scoring intent but it can have many entities. 
+The intent represents action the application should take for the user and is based on the entire utterance. An utterance can have only one top scoring intent but it can have many entities.
 
 <a name="how-do-intents-relate-to-entities"></a>
 
-Create an intent when the user's _intention_ would trigger an action in your client application, like a call to the checkweather() function. Then create entities to represent parameters required to execute the action. 
+Create an intent when the user's _intention_ would trigger an action in your client application, like a call to the checkweather() function. Then create entities to represent parameters required to execute the action.
 
-|Intent   | Entity | Example utterance   | 
+|Intent   | Entity | Example utterance   |
 |------------------|------------------------------|------------------------------|
 | CheckWeather | { "type": "location", "entity": "seattle" }<br>{ "type": "builtin.datetimeV2.date","entity": "tomorrow","resolution":"2018-05-23" } | What's the weather like in `Seattle` `tomorrow`? |
-| CheckWeather | { "type": "date_range", "entity": "this weekend" } | Show me the forecast for `this weekend` | 
+| CheckWeather | { "type": "date_range", "entity": "this weekend" } | Show me the forecast for `this weekend` |
 ||||
 
 ## Prebuilt domain intents
 
-[Prebuilt domains](luis-how-to-use-prebuilt-domains.md) provide intents with utterances. 
+[Prebuilt domains](luis-how-to-use-prebuilt-domains.md) provide intents with utterances.
 
 ## None intent
 
 The **None** intent is created but left empty on purpose. The **None** intent is a required intent and can't be deleted or renamed. Fill it with utterances that are outside of your domain.
 
-The **None** intent is the fallback intent, important in every app, and should have 10% of the total utterances. It is used to teach LUIS utterances that are not important in the app domain (subject area). If you do not add any utterances for the **None** intent, LUIS forces an utterance that is outside the domain into one of the domain intents. This will skew the prediction scores by teaching LUIS the wrong intent for the utterance. 
+The **None** intent is the fallback intent, important in every app, and should have 10% of the total utterances. It is used to teach LUIS utterances that are not important in the app domain (subject area). If you do not add any utterances for the **None** intent, LUIS forces an utterance that is outside the domain into one of the domain intents. This will skew the prediction scores by teaching LUIS the wrong intent for the utterance.
 
-When an utterance is predicted as the None intent, the client application can ask more questions or provide a menu to direct the user to valid choices. 
+When an utterance is predicted as the None intent, the client application can ask more questions or provide a menu to direct the user to valid choices.
 
-## Negative intentions 
-If you want to determine negative and positive intentions, such as "I **want** a car" and "I **don't** want a car", you can create two intents (one positive, and one negative) and add appropriate utterances for each. Or you can create a single intent and mark the two different positive and negative terms as an entity.  
+## Negative intentions
+If you want to determine negative and positive intentions, such as "I **want** a car" and "I **don't** want a car", you can create two intents (one positive, and one negative) and add appropriate utterances for each. Or you can create a single intent and mark the two different positive and negative terms as an entity.
 
 ## Intents and patterns
 
-If you have example utterances, which can be defined in part or whole as a regular expression, consider using the [regular expression entity](luis-concept-entity-types.md#regular-expression-entity) paired with a [pattern](luis-concept-patterns.md). 
+If you have example utterances, which can be defined in part or whole as a regular expression, consider using the [regular expression entity](luis-concept-entity-types.md#regular-expression-entity) paired with a [pattern](luis-concept-patterns.md).
 
-Using a regular expression entity guarantees the data extraction so that the pattern is matched. The pattern matching guarantees an exact intent is returned. 
+Using a regular expression entity guarantees the data extraction so that the pattern is matched. The pattern matching guarantees an exact intent is returned.
 
 ## Intent balance
-The app domain intents should have a balance of utterances across each intent. Do not have one intent with 10 utterances and another intent with 500 utterances. This is not balanced. If you have this situation, review the intent with 500 utterances to see if many of the intents can be reorganized into a [pattern](luis-concept-patterns.md). 
+The app domain intents should have a balance of utterances across each intent. Do not have one intent with 10 utterances and another intent with 500 utterances. This is not balanced. If you have this situation, review the intent with 500 utterances to see if many of the intents can be reorganized into a [pattern](luis-concept-patterns.md).
 
 The **None** intent is not included in the balance. That intent should contain 10% of the total utterances in the app.
 
 ## Intent limits
-Review [limits](luis-boundaries.md#model-boundaries) to understand how many intents you can add to a model. 
+Review [limits](luis-limits.md#model-boundaries) to understand how many intents you can add to a model.
 
-### If you need more than the maximum number of intents 
-First, consider whether your system is using too many intents. 
+### If you need more than the maximum number of intents
+First, consider whether your system is using too many intents.
 
-### Can multiple intents be combined into single intent with entities 
-Intents that are too similar can make it more difficult for LUIS to distinguish between them. Intents should be varied enough to capture the main tasks that the user is asking for, but they don't need to capture every path your code takes. For example, BookFlight and FlightCustomerService might be separate intents in a travel app, but BookInternationalFlight and BookDomesticFlight are too similar. If your system needs to distinguish them, use entities or other logic rather than intents. 
+### Can multiple intents be combined into single intent with entities
+Intents that are too similar can make it more difficult for LUIS to distinguish between them. Intents should be varied enough to capture the main tasks that the user is asking for, but they don't need to capture every path your code takes. For example, BookFlight and FlightCustomerService might be separate intents in a travel app, but BookInternationalFlight and BookDomesticFlight are too similar. If your system needs to distinguish them, use entities or other logic rather than intents.
 
 ### Dispatcher model
-Learn more about combining LUIS and QnA maker apps with the [dispatch model](luis-concept-enterprise.md#when-you-need-to-combine-several-luis-and-qna-maker-apps). 
+Learn more about combining LUIS and QnA maker apps with the [dispatch model](luis-concept-enterprise.md#when-you-need-to-combine-several-luis-and-qna-maker-apps).
 
 ### Request help for apps with significant number of intents
-If reducing the number of intents or dividing your intents into multiple apps doesn't work for you, contact support. If your Azure subscription includes support services, contact [Azure technical support](https://azure.microsoft.com/support/options/). 
+If reducing the number of intents or dividing your intents into multiple apps doesn't work for you, contact support. If your Azure subscription includes support services, contact [Azure technical support](https://azure.microsoft.com/support/options/).
 
 ## Next steps