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‎articles/cognitive-services/text-analytics/how-tos/text-analytics-how-to-entity-linking.md

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ms.service: cognitive-services
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ms.subservice: text-analytics
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ms.topic: article
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ms.date: 01/27/2019
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ms.date: 02/10/2020
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ms.author: aahi
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---
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See [language support](../language-support.md#sentiment-analysis-key-phrase-extraction-and-named-entity-recognition) for information.
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#### [Version 3.0-preview](#tab/version-3)
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### Entity types
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Named Entity Recognition v3 provides expanded detection across multiple types. Currently, NER v3 can recognize the following categories of entities:
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* General
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* Personal Information
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For a detailed list of supported entities and languages, see the [NER v3 supported entity types](../named-entity-types.md) article.
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### Request endpoints
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Named Entity Recognition v3 uses separate endpoints for NER and entity linking requests. Use a URL format below based on your request:
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NER
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* General entities - `https://<your-custom-subdomain>.cognitiveservices.azure.com/text/analytics/v3.0-preview.1/entities/recognition/general`
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* Personal information - `https://<your-custom-subdomain>.cognitiveservices.azure.com/text/analytics/v3.0-preview.1/entities/recognition/pii`
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Entity linking
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* `https://<your-custom-subdomain>.cognitiveservices.azure.com/text/analytics/v3.0-preview.1/entities/linking`
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### Model versioning
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[!INCLUDE [v3-model-versioning](../includes/model-versioning.md)]
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#### [Version 2](#tab/version-2)
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### Entity types
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`https://<your-custom-subdomain>.cognitiveservices.azure.com/text/analytics/v2.1/entities`
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#### [Version 3 (Public preview)](#tab/version-3)
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### Entity types
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Named Entity Recognition v3 provides expanded detection across multiple types. Currently, NER v3 can recognize the following categories of entities:
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* General
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* Personal Information
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For a detailed list of supported entities and languages, see the [NER v3 supported entity types](../named-entity-types.md) article.
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### Request endpoints
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Named Entity Recognition v3 uses separate endpoints for NER and entity linking requests. Use a URL format below based on your request:
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NER
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* General entities - `https://<your-custom-subdomain>.cognitiveservices.azure.com/text/analytics/v3.0-preview.1/entities/recognition/general`
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* Personal information - `https://<your-custom-subdomain>.cognitiveservices.azure.com/text/analytics/v3.0-preview.1/entities/recognition/pii`
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Entity linking
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* `https://<your-custom-subdomain>.cognitiveservices.azure.com/text/analytics/v3.0-preview.1/entities/linking`
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### Model versioning
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[!INCLUDE [v3-model-versioning](../includes/model-versioning.md)]
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## Sending a REST API request
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[!INCLUDE [text-analytics-find-resource-information](../includes/find-azure-resource-info.md)]
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#### [Version 2](#tab/version-2)
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[Named Entity Recognition (NER) v2 reference](https://eastus.dev.cognitive.microsoft.com/docs/services/TextAnalytics-v2-1/operations/5ac4251d5b4ccd1554da7634)
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Version 2 uses the following endpoint for entity linking and NER requests:
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`https://<your-custom-subdomain>.cognitiveservices.azure.com/text/analytics/v2.1/entities`
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#### [Version 3](#tab/version-3)
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#### [Version 3.0-preview](#tab/version-3)
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[Named Entity Recognition v3 reference](https://westus.dev.cognitive.microsoft.com/docs/services/TextAnalytics-v3-0-Preview-1/operations/EntitiesRecognitionGeneral)
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Entity linking
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* `https://<your-custom-subdomain>.cognitiveservices.azure.com/text/analytics/v3.0-preview.1/entities/linking`
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#### [Version 2](#tab/version-2)
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[Named Entity Recognition (NER) v2 reference](https://eastus.dev.cognitive.microsoft.com/docs/services/TextAnalytics-v2-1/operations/5ac4251d5b4ccd1554da7634)
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Version 2 uses the following endpoint for entity linking and NER requests:
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`https://<your-custom-subdomain>.cognitiveservices.azure.com/text/analytics/v2.1/entities`
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---
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Set a request header to include your Text Analytics API key. In the request body, provide the JSON documents you prepared.
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Output is returned immediately. You can stream the results to an application that accepts JSON or save the output to a file on the local system, and then import it into an application that allows you to sort, search, and manipulate the data.
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#### [Version 2](#tab/version-2)
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### Example NER v2 response
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```json
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{
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"documents": [{
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"id": "1",
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"entities": [{
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"name": "Seattle",
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"matches": [{
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"wikipediaScore": 0.15046201222847677,
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"entityTypeScore": 0.80624294281005859,
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"text": "Seattle",
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"offset": 26,
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"length": 7
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}],
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"wikipediaLanguage": "en",
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"wikipediaId": "Seattle",
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"wikipediaUrl": "https://en.wikipedia.org/wiki/Seattle",
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"bingId": "5fbba6b8-85e1-4d41-9444-d9055436e473",
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"type": "Location"
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}, {
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"name": "last week",
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"matches": [{
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"entityTypeScore": 0.8,
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"text": "last week",
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"offset": 34,
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"length": 9
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}],
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"type": "DateTime",
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"subType": "DateRange"
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}]
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}],
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"errors": []
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}
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```
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#### [Version 3 (Public preview)](#tab/version-3)
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#### [Version 3.0-preview)](#tab/version-3)
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### Example v3 responses
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}
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```
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#### [Version 2](#tab/version-2)
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### Example NER v2 response
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```json
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{
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"documents": [{
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"id": "1",
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"entities": [{
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"name": "Seattle",
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"matches": [{
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"wikipediaScore": 0.15046201222847677,
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"entityTypeScore": 0.80624294281005859,
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"text": "Seattle",
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"offset": 26,
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"length": 7
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}],
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"wikipediaLanguage": "en",
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"wikipediaId": "Seattle",
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"wikipediaUrl": "https://en.wikipedia.org/wiki/Seattle",
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"bingId": "5fbba6b8-85e1-4d41-9444-d9055436e473",
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"type": "Location"
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}, {
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"name": "last week",
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"matches": [{
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"entityTypeScore": 0.8,
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"text": "last week",
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"offset": 34,
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"length": 9
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}],
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"type": "DateTime",
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"subType": "DateRange"
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}]
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}],
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"errors": []
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}
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```
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## Summary

‎articles/cognitive-services/text-analytics/how-tos/text-analytics-how-to-sentiment-analysis.md

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ms.service: cognitive-services
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ms.subservice: text-analytics
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ms.topic: sample
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ms.date: 12/17/2019
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ms.date: 02/10/2020
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ms.author: aahi
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| Sentiment labeling | | X |
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| Model versioning | | X |
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#### [Version 2](#tab/version-2)
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### Sentiment scoring
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The sentiment analyzer classifies text as predominantly positive or negative. It assigns a score in the range of 0 to 1. Values close to 0.5 are neutral or indeterminate. A score of 0.5 indicates neutrality. When a string can't be analyzed for sentiment or has no sentiment, the score is always 0.5 exactly. For example, if you pass in a Spanish string with an English language code, the score is 0.5.
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#### [Version 3 (Public preview)](#tab/version-3)
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#### [Version 3.0-preview](#tab/version-3)
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### Sentiment scoring
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You can find an example C# application that calls this version of Sentiment Analysis on [GitHub](https://github.com/Azure-Samples/cognitive-services-REST-api-samples/tree/master/dotnet/Language/SentimentV3.cs).
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#### [Version 2](#tab/version-2)
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### Sentiment scoring
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The sentiment analyzer classifies text as predominantly positive or negative. It assigns a score in the range of 0 to 1. Values close to 0.5 are neutral or indeterminate. A score of 0.5 indicates neutrality. When a string can't be analyzed for sentiment or has no sentiment, the score is always 0.5 exactly. For example, if you pass in a Spanish string with an English language code, the score is 0.5.
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## Sending a REST API request
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Create a POST request. You can [use Postman](text-analytics-how-to-call-api.md) or the **API testing console** in the following reference links to quickly structure and send one.
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#### [Version 2](#tab/version-2)
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#### [Version 3.0-preview](#tab/version-3)
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[Sentiment Analysis v2 reference](https://westcentralus.dev.cognitive.microsoft.com/docs/services/TextAnalytics-v2-1/operations/56f30ceeeda5650db055a3c9)
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[Sentiment Analysis v3 reference](https://westus.dev.cognitive.microsoft.com/docs/services/TextAnalytics-v3-0-Preview-1/operations/Sentiment)
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#### [Version 3 (Public preview)](#tab/version-3)
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#### [Version 2](#tab/version-2)
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[Sentiment Analysis v3 reference](https://westus.dev.cognitive.microsoft.com/docs/services/TextAnalytics-v3-0-Preview-1/operations/Sentiment)
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[Sentiment Analysis v2 reference](https://westcentralus.dev.cognitive.microsoft.com/docs/services/TextAnalytics-v2-1/operations/56f30ceeeda5650db055a3c9)
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Set the HTTPS endpoint for sentiment analysis by using either a Text Analytics resource on Azure or an instantiated [Text Analytics container](text-analytics-how-to-install-containers.md). You must include the correct URL for the version you want to use. For example:
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#### [Version 2](#tab/version-2)
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#### [Version 3.0-preview](#tab/version-3)
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`https://<your-custom-subdomain>.cognitiveservices.azure.com/text/analytics/v2.1/sentiment`
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`https://<your-custom-subdomain>.cognitiveservices.azure.com/text/analytics/v3.0-preview.1/sentiment`
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#### [Version 3 (Public preview)](#tab/version-3)
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#### [Version 2](#tab/version-2)
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`https://<your-custom-subdomain>.cognitiveservices.azure.com/text/analytics/v2.1/sentiment`
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Output is returned immediately. You can stream the results to an application that accepts JSON or save the output to a file on the local system. Then, import the output into an application that you can use to sort, search, and manipulate the data.
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#### [Version 2](#tab/version-2)
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### Sentiment Analysis v2 example response
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Responses from Sentiment Analysis v2 contain sentiment scores for each sent document.
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```json
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{
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"documents": [{
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"id": "1",
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"score": 0.98690706491470337
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"id": "2",
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"score": 0.95202046632766724
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}],
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"errors": []
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}
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```
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#### [Version 3.0-preview](#tab/version-3)
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```
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#### [Version 2](#tab/version-2)
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### Sentiment Analysis v2 example response
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Responses from Sentiment Analysis v2 contain sentiment scores for each sent document.
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```json
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{
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"documents": [{
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"id": "1",
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"score": 0.98690706491470337
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}, {
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"id": "2",
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"score": 0.95202046632766724
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}],
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"errors": []
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}
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```
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## Summary

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