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    Text Analytics

    Detect sentiment, key phrases, and language from your text

    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:
    Seattle, wonderful trip, Space Needle
    Sentiment:
    98 %
    Entities:
    Seattle [Location]
    Space Needle [Location]
    Named Entity Recognition:
    I had a wonderful trip to Seattle and enjoyed seeing the Space Needle!
    {
      "languageDetection": {
        "documents": [
          {
            "id": "37957af0-3985-4c62-a070-ef81811870cd",
            "detectedLanguages": [
              {
                "name": "English",
                "iso6391Name": "en",
                "score": 1.0
              }
            ]
          }
        ],
        "errors": []
      },
      "keyPhrases": {
        "documents": [
          {
            "id": "37957af0-3985-4c62-a070-ef81811870cd",
            "keyPhrases": [
              "Seattle",
              "wonderful trip",
              "Space Needle"
            ]
          }
        ],
        "errors": []
      },
      "sentiment": {
        "documents": [
          {
            "id": "37957af0-3985-4c62-a070-ef81811870cd",
            "score": 0.97037649154663086
          }
        ],
        "errors": []
      },
      "entities": {
        "documents": [
          {
            "id": "37957af0-3985-4c62-a070-ef81811870cd",
            "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"
              },
              {
                "name": "Space Needle",
                "matches": [
                  {
                    "text": "Space Needle",
                    "offset": 57,
                    "length": 12
                  }
                ],
                "wikipediaLanguage": "en",
                "wikipediaId": "Space Needle",
                "wikipediaUrl": "https://en.wikipedia.org/wiki/Space_Needle",
                "bingId": "f8dd5b08-206d-2554-6e4a-893f51f4de7e",
                "type": "Location"
              }
            ]
          }
        ],
        "errors": []
      }
    }

    Want to build this?

    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
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