Text Analytics API | Microsoft Azure





Detect sentiment, key phrases, named entities and language from your text




















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Extract information from your text

Use the demo below to experiment with the Text Analytics API. Pick one of our examples or provide
your own. Identify the language, sentiment, key phrases, and entities (Preview) of your text by clicking “Analyze”.



See it in action






  1. Analyzed text
  2. JSON







Languages: English (confidence: 100 %)
Key phrases: week, Space Needle, wonderful trip, Seattle, times
Sentiment:
Named Entities: Seattle [Location]
last week [DateTime-DateRange]
Space Needle [Location]
Space Needle [Organization]
2 [Quantity-Number]
Linked Entities: I had a wonderful trip to Seattle last week and even visited the Space Needle 2 times!



{
“languageDetection”: {
“documents”: [
{
“id”: “736d35e8-0de8-4c0e-9a2a-b57786d26c03”,
“detectedLanguages”: [
{
“name”: “English”,
“iso6391Name”: “en”,
“score”: 1.0
}
]
}
],
“errors”: []
},
“keyPhrases”: {
“documents”: [
{
“id”: “736d35e8-0de8-4c0e-9a2a-b57786d26c03”,
“keyPhrases”: [
“week”,
“Space Needle”,
“wonderful trip”,
“Seattle”,
“times”
]
}
],
“errors”: []
},
“sentiment”: {
“documents”: [
{
“id”: “736d35e8-0de8-4c0e-9a2a-b57786d26c03”,
“score”: 0.83725243806838989
}
],
“errors”: []
},
“entities”: {
“documents”: [
{
“id”: “736d35e8-0de8-4c0e-9a2a-b57786d26c03”,
“entities”: [
{
“name”: “Seattle”,
“matches”: [
{
“text”: “Seattle”,
“offset”: 26,
“length”: 7
}
],
“wikipediaLanguage”: “en”,
“wikipediaId”: “Seattle”,
“wikipediaUrl”: “https://en.wikipedia.org/wiki/Seattle”,
“bingId”: “5fbba6b8-85e1-4d41-9444-d9055436e473”,
“type”: “Location”,
“subType”: null
},
{
“name”: “last week”,
“matches”: [
{
“text”: “last week”,
“offset”: 34,
“length”: 9
}
],
“wikipediaLanguage”: null,
“wikipediaId”: null,
“wikipediaUrl”: null,
“bingId”: null,
“type”: “DateTime”,
“subType”: “DateRange”
},
{
“name”: “Space Needle”,
“matches”: [
{
“text”: “Space Needle”,
“offset”: 65,
“length”: 12
}
],
“wikipediaLanguage”: “en”,
“wikipediaId”: “Space Needle”,
“wikipediaUrl”: “https://en.wikipedia.org/wiki/Space_Needle”,
“bingId”: “f8dd5b08-206d-2554-6e4a-893f51f4de7e”,
“type”: “Location”,
“subType”: null
},
{
“name”: “Space Needle”,
“matches”: [
{
“text”: “Space Needle”,
“offset”: 65,
“length”: 12
}
],
“wikipediaLanguage”: null,
“wikipediaId”: null,
“wikipediaUrl”: null,
“bingId”: null,
“type”: “Organization”,
“subType”: null
},
{
“name”: “2”,
“matches”: [
{
“text”: “2”,
“offset”: 78,
“length”: 1
}
],
“wikipediaLanguage”: null,
“wikipediaId”: null,
“wikipediaUrl”: null,
“bingId”: null,
“type”: “Quantity”,
“subType”: “Number”
}
]
}
],
“errors”: []
}
}












Sentiment analysis

The API returns a numeric score between 0 and 1. Scores close to 1 indicate positive sentiment, and scores close to 0 indicate negative sentiment. Sentiment score is generated using classification techniques. The input features of the classifier include n-grams, features generated from part-of-speech tags, and word embeddings. It is supported in a variety of languages.


Learn more





Key phrase extraction


The API returns a list of strings denoting the key talking points in the input text.

We employ techniques from
Microsoft Office’s sophisticated Natural Language Processing toolkit. English, German, Spanish, and Japanese text are
supported.


Learn more





Language detection

The API returns the detected language and a numeric score between 0 and 1. Scores close to 1 indicate 100%
certainty that the identified language is true. A total of 120 languages are supported.


Learn more





Named Entity Recognition

Detect all named entities in the text, such as organizations, people, and locations, and more. Entity Linking disambiguates distinct entities by associating text to additional information on the web. For example, use it to determine whether a term such as “times” refers to “The New York Times” or “Times Square.”

Learn more







Prism Skylabs

“We found Cognitive Services to be the missing piece in the equation, the one that we needed to bring this solution to market and really revolutionize the way people look at video.”


Katie McCann: Vice President of Product and Engineering | Prism Skylabs








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