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title: Text Analytics API overview - Azure Cognitive Services | Microsoft Docs
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description: Text Analytics API in Azure Cognitive Services for sentiment analysis, key phrase extraction, and language detection.
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title: Text Analytics overview - Azure Cognitive Services | Microsoft Docs
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description: Text Analytics in Azure Cognitive Services for sentiment analysis, key phrase extraction, language detection, and entity linking.
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services: cognitive-services
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author: ashmaka
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manager: cgronlun
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ms.date: 5/02/2018
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ms.author: ashmaka
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---
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# What is Text Analytics API Version 2.0?
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The Text Analytics API is a cloud-based service that provides advanced natural language processing over raw text, and includes four main functions: sentiment analysis, key phrase extraction, language detection, and entity linking.
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# What is Text Analytics?
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The API is backed by resources in [Microsoft Cognitive Services](https://docs.microsoft.com/azure/cognitive-services/), a collection of machine learning and AI algorithms in the cloud, readily consumable in your development projects.
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The Text Analytics service provides advanced natural language processing for raw unstructured text. It includes four main functions: sentiment analysis, key phrase extraction, language detection, and entity linking.
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The Text Analytics API provides four types of analysis: sentiment analysis, key phrase extraction, .
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## Analyze sentiment
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## Sentiment Analysis
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[Find out](how-tos/text-analytics-how-to-sentiment-analysis.md) what customers think of your brand or topic by analyzing raw text for clues about positive or negative sentiment. This API returns a sentiment score between 0 and 1 for each document, where 1 is the most positive.<br />
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The analysis models are pretrained using an extensive body of text and natural language technologies from Microsoft. For [selected languages](text-analytics-supported-languages.md), the API can analyze and score any raw text that you provide.
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[Find out](how-tos/text-analytics-how-to-sentiment-analysis.md) what customers think of your brand or topic by analyzing raw text for clues about positive or negative sentiment. This API returns a sentiment score between 0 and 1 for each document, where 1 is the most positive.<br /> The analysis models are pretrained using an extensive body of text and natural language technologies from Microsoft. For [selected languages](text-analytics-supported-languages.md), the API can analyze and score any raw text that you provide, directly returning results to the calling application.
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## Extract key phrases
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## Key Phrase Extraction
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Automatically [extract key phrases](how-tos/text-analytics-how-to-keyword-extraction.md) to quickly identify the main points. For example, given the input text "The food was delicious and there were wonderful staff", the Text Analytics service returns the main talking points: "food" and "wonderful staff".
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Automatically [extract key phrases](how-tos/text-analytics-how-to-keyword-extraction.md) to quickly identify the main points. For example, for the input text "The food was delicious and there were wonderful staff", the API returns the main talking points: "food" and "wonderful staff".
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## Language Detection
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## Detect language
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For up to 120 languages, [detect](how-tos/text-analytics-how-to-language-detection.md) which language the input text is written in and report a single language code for every document submitted on the request. The language code is paired with a score indicating the strength of the score.
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## Entity Linking (Preview)
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## Idenfity linked entities (Preview)
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[Identify](how-tos/text-analytics-how-to-entity-linking.md) well-known entities in your text and link to more information on the web. Entity linking recognizes and disambiguates when a term is used as one of separately distinguishable entities, verbs, and other word forms.
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1.[Sign up](https://docs.microsoft.com/azure/cognitive-services/cognitive-services-apis-create-account) for an [access key](how-tos/text-analytics-how-to-access-key.md). The key must be passed on each request.
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2.[Formulate a request](how-tos/text-analytics-how-to-call-api.md#json-schema)containing your data as raw unstructured text, in JSON.
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2.[Create a request](how-tos/text-analytics-how-to-call-api.md#json-schema)in JSON that contains your data as raw unstructured text.
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3. Post the request to the endpoint established during sign-up, appending the desired resource: sentiment analysis, key phrase extraction, language detection, or entity identification.
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4. Stream or store the response locally. Depending on the request, results are either a sentiment score, a collection of extracted key phrases, or a language code.
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Output is returned as a single JSON document, with results for each text document you posted, based on ID. You can subsequently analyze, visualize, or categorize the results into actionable insights.
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Data is not stored in your account. Operations performed by the Text Analytics API are stateless, which means the text you provide is processed and results are returned immediately.
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Data is not stored in your account. Operations performed by the Text Analytics service are stateless, which means the text you provide is processed and results are returned immediately.
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<aname="supported-languages"></a>
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<aname="data-limits"></a>
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## Supported languages
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## Specifications
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This section has been moved to a separate article for better discoverability. Refer to [Supported languages in Text Analytics API](text-analytics-supported-languages.md) for this content.
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### Supported languages
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<aname="data-limits"></a>
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Please see [Supported languages in Text Analytics](text-analytics-supported-languages.md).
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## Data limits
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###Data limits
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All of the Text Analytics API endpoints accept raw text data. The current limit is 5,000 characters for each document; if you need to analyze larger documents, you can break them up into smaller chunks. If you still require a higher limit, [contact us](https://azure.microsoft.com/overview/sales-number/) so that we can discuss your requirements.
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All of the Text Analytics service endpoints accept raw text data. The current limit is 5,000 characters for each document; if you need to analyze larger documents, you can break them up into smaller chunks. If you still require a higher limit, [contact us](https://azure.microsoft.com/overview/sales-number/) so that we can discuss your requirements.
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| Limit | Value |
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|------------------------|---------------|
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| Maximum size of a single document | 5,000 characters as measured by `String.Length`. |
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| Maximum size of entire request | 1 MB |
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| Maximum number of documents in a request | 1,000 documents |
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The rate limit is 100 calls per minute. Note that you can submit a large quantity of documents in a single call (up to 1000 documents).
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The rate limit is 100 calls per minute. Note you can submit a large quantity of documents in a single call (up to 1000 documents).
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## Unicode encoding
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###Unicode encoding
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The Text Analytics API uses Unicode encoding for text representation and character count calculations. Requests can be submitted in both UTF-8 and UTF-16 with no measurable differences in the character count. Unicode codepoints are used as the heuristic for character length and are considered equivalent for the purposes of text analytics data limits. If you use `String.Length` to get the character count, you are using the same method we use to measure data size.
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## Next steps
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First, try the [interactive demo](https://azure.microsoft.com/services/cognitive-services/text-analytics/). You can paste a text input (5,000 character maximum) to detect the language (up to 120), calculate a sentiment score, or extract key phrases. No sign-up necessary.
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First, try the [interactive demo](https://azure.microsoft.com/services/cognitive-services/text-analytics/). You can paste a text input (5,000 character maximum) to detect the language (up to 120), calculate a sentiment score, extract key phrases, or identify linked entities. No sign-up is necessary.
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When you are ready to call the API directly:
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When you are ready to call the Text Analytics service directly:
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+[Sign up](how-tos/text-analytics-how-to-signup.md) for an access key and review the steps for [calling the API](how-tos/text-analytics-how-to-call-api.md).
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