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articles/active-directory/app-provisioning/skip-out-of-scope-deletions.md

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Here's the JSON block to add to the mapping.
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```json
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{
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"key": "SkipOutOfScopeDeletions",
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"value": "True"
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}
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{
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"key": "SkipOutOfScopeDeletions",
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"value": "True"
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}
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```
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## Step 4: Update the secrets endpoint with the SkipOutOfScopeDeletions flag

articles/active-directory/manage-apps/restore-application.md

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:::zone pivot="ms-graph"
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1. To restore the enterprise application, run the following query:
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To restore the enterprise application, run the following query:
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# [HTTP](#tab/http)
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```http
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POST https://graph.microsoft.com/v1.0/directory/deletedItems/{id}/restore
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```
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# [C#](#tab/csharp)
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[!INCLUDE [sample-code](~/microsoft-graph/api-reference/v1.0/includes/snippets/csharp/restore-directory-deleteditem-csharp-snippets.md)]
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# [JavaScript](#tab/javascript)
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[!INCLUDE [sample-code](~/microsoft-graph/api-reference/v1.0/includes/snippets/javascript/restore-directory-deleteditem-javascript-snippets.md)]
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# [Java](#tab/java)
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[!INCLUDE [sample-code](~/microsoft-graph/api-reference/v1.0/includes/snippets/java/restore-directory-deleteditem-java-snippets.md)]
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# [Go](#tab/go)
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[!INCLUDE [sample-code](~/microsoft-graph/api-reference/v1.0/includes/snippets/go/restore-directory-deleteditem-go-snippets.md)]
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# [PowerShell](#tab/powershell)
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[!INCLUDE [sample-code](~/microsoft-graph/api-reference/v1.0/includes/snippets/powershell/restore-directory-deleteditem-powershell-snippets.md)]
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# [PHP](#tab/php)
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[!INCLUDE [sample-code](~/microsoft-graph/api-reference/v1.0/includes/snippets/php/restore-directory-deleteditem-php-snippets.md)]
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---
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Replace ID with the object ID of the service principal that you want to restore.
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:::zone-end

articles/ai-services/LUIS/luis-tutorial-node-import-utterances-csv.md

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For example, the entry for "Turn on the lights" maps to this JSON:
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```json
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{
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"text": "Turn on the lights",
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"intentName": "TurnOn",
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"entityLabels": [
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{
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"text": "Turn on the lights",
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"intentName": "TurnOn",
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"entityLabels": [
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{
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"entityName": "Operation",
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"startCharIndex": 5,
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"endCharIndex": 6
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},
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{
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"entityName": "Device",
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"startCharIndex": 12,
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"endCharIndex": 17
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}
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]
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"entityName": "Operation",
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"startCharIndex": 5,
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"endCharIndex": 6
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},
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{
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"entityName": "Device",
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"startCharIndex": 12,
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"endCharIndex": 17
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}
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]
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}
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```
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In this example, the `intentName` comes from the user request under the **Request** column heading in the CSV file, and the `entityName` comes from the other columns with key information. For example, if there's an entry for **Operation** or **Device**, and that string also occurs in the actual request, then it can be labeled as an entity. The following code demonstrates this parsing process. You can copy or [download](https://github.com/Azure-Samples/cognitive-services-language-understanding/blob/master/examples/build-app-programmatically-csv/_parse.js) it and save it to `_parse.js`.

articles/ai-services/language-service/text-analytics-for-health/concepts/relation-extraction.md

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Relation extraction output contains URI references and assigned roles of the entities of the relation type. For example, in the following JSON:
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```json
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"relations": [
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{
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"relationType": "DosageOfMedication",
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"entities": [
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{
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"ref": "#/results/documents/0/entities/0",
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"role": "Dosage"
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},
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{
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"ref": "#/results/documents/0/entities/1",
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"role": "Medication"
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}
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]
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},
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{
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"relationType": "RouteOfMedication",
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"entities": [
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{
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"ref": "#/results/documents/0/entities/1",
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"role": "Medication"
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},
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{
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"ref": "#/results/documents/0/entities/2",
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"role": "Route"
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}
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]
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...
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"relations": [
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{
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"relationType": "DosageOfMedication",
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"entities": [
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{
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"ref": "#/results/documents/0/entities/0",
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"role": "Dosage"
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},
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{
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"ref": "#/results/documents/0/entities/1",
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"role": "Medication"
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}
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]
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},
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{
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"relationType": "RouteOfMedication",
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"entities": [
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{
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"ref": "#/results/documents/0/entities/1",
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"role": "Medication"
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},
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{
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"ref": "#/results/documents/0/entities/2",
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"role": "Route"
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}
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]
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}
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]
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```
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articles/ai-services/speech-service/speech-synthesis-markup-pronunciation.md

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| `ordinal` | None | The text is spoken as an ordinal number. The speech synthesis engine pronounces:<br /><br />`Select the <say-as interpret-as="ordinal">3rd</say-as> option`<br /><br />As "Select the third option."|
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| `number_digit` | None | The text is spoken as a sequence of individual digits. The speech synthesis engine pronounces:<br /><br />`<say-as interpret-as="number_digit">123456789</say-as>`<br /><br />As "1 2 3 4 5 6 7 8 9." |
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| `fraction` | None | The text is spoken as a fractional number. The speech synthesis engine pronounces:<br /><br /> `<say-as interpret-as="fraction">3/8</say-as> of an inch`<br /><br />As "three eighths of an inch." |
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| `date` | dmy, mdy, ymd, ydm, ym, my, md, dm, d, m, y | The text is spoken as a date. The `format` attribute specifies the date's format (*d=day, m=month, and y=year*). The speech synthesis engine pronounces:<br /><br />`Today is <say-as interpret-as="date" format="mdy">10-19-2016</say-as>`<br /><br />As "Today is October nineteenth two thousand sixteen." |
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| `date` | dmy, mdy, ymd, ydm, ym, my, md, dm, d, m, y | The text is spoken as a date. The `format` attribute specifies the date's format (*d=day, m=month, and y=year*). The speech synthesis engine pronounces:<br /><br />`Today is <say-as interpret-as="date">10-12-2016</say-as>`<br /><br />As "Today is October twelfth two thousand sixteen."<br />Pronounces:<br /><br />`Today is <say-as interpret-as="date" format="dmy">10-12-2016</say-as>`<br /><br />As "Today is December tenth two thousand sixteen." |
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| `time` | hms12, hms24 | The text is spoken as a time. The `format` attribute specifies whether the time is specified by using a 12-hour clock (hms12) or a 24-hour clock (hms24). Use a colon to separate numbers representing hours, minutes, and seconds. Here are some valid time examples: 12:35, 1:14:32, 08:15, and 02:50:45. The speech synthesis engine pronounces:<br /><br />`The train departs at <say-as interpret-as="time" format="hms12">4:00am</say-as>`<br /><br />As "The train departs at four A M." |
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| `duration` | hms, hm, ms | The text is spoken as a duration. The `format` attribute specifies the duration's format (*h=hour, m=minute, and s=second*). The speech synthesis engine pronounces:<br /><br />`<say-as interpret-as="duration">01:18:30</say-as>`<br /><br /> As "one hour eighteen minutes and thirty seconds".<br />Pronounces:<br /><br />`<say-as interpret-as="duration" format="ms">01:18</say-as>`<br /><br /> As "one minute and eighteen seconds".<br />This tag is only supported on English and Spanish. |
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| `telephone` | None | The text is spoken as a telephone number. The speech synthesis engine pronounces:<br /><br />`The number is <say-as interpret-as="telephone">(888) 555-1212</say-as>`<br /><br />As "My number is area code eight eight eight five five five one two one two." |

articles/aks/image-cleaner.md

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name: imagelist
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spec:
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images:
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- docker.io/library/alpine:3.7.3 # You can also use "*" to specify all non-running images
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- docker.io/library/alpine:3.7.3
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// You can also use "*" to specify all non-running images
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```
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2. Apply the `ImageList` to your cluster using the `kubectl apply` command.

articles/azure-maps/how-to-manage-pricing-tier.md

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:::image type="content" source="./media/how-to-manage-pricing-tier/arm-template.png" border="true" alt-text="Screenshot of an ARM template that demonstrates updating pricingTier to G2 and kind to Gen2.":::
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```json
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"pricingTier": {
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"type": "string",
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"allowedValues":[
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"G2"
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],
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"defaultValue": "G2",
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"metadata": {
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"description": "The pricing tier SKU for the account."
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}
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},
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"kind": {
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"type": "string",
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"allowedValues":[
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"Gen2"
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],
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"defaultValue": "Gen2",
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"metadata": {
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"description": "The pricing tier for the account."
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}
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}
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"pricingTier": {
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"type": "string",
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"allowedValues":[
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"G2"
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],
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"defaultValue": "G2",
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"metadata": {
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"description": "The pricing tier SKU for the account."
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}
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},
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"kind": {
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"type": "string",
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"allowedValues":[
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"Gen2"
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],
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"defaultValue": "Gen2",
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"metadata": {
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"description": "The pricing tier for the account."
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}
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}
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```
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:::code language="json" source="~/quickstart-templates/quickstarts/microsoft.maps/maps-create/azuredeploy.json" range="27-46":::
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--->

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