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Text Analytics

A text-mining AI service that uncovers insights such as sentiment analysis, entities, relations, and key phrases in unstructured text

Mine insights from text

Mine insights in unstructured text using natural language processing (NLP)—no machine learning expertise required. Gain a deeper understanding of customer opinions with sentiment analysis. Identify key phrases and entities such as people, places, and organizations to understand common topics and trends. Classify medical terminology using domain-specific, pretrained models. Evaluate text in a wide range of languages.

Broad entity extraction

Identify important concepts in text, including key phrases and named entities such as people, events, and organizations.

Powerful sentiment analysis

Examine what customers are saying about your brand and analyze sentiments around specific topics through opinion mining.

Question answering

Get answers to questions from content such as FAQ, product manuals, blogs, and policies.

Process medical text

Extract and process real-time and batch analysis of insights stored in unstructured medical text.

Languages: English (confidence: 100 %)
Key phrases: The Sirloin steak, Contoso Steakhouse, midtown NYC, dinner party, great menu, chief cook, John Doe, online menu, marvelous food, spot, owner, name, kitchen, dining, place, order, contososteakhouse, email, complaint
Sentiment:
Document
MIXED
86%
Positive
0%
Neutral
14%
Negative
Sentence 1
POSITIVE
99%
Positive
1%
Neutral
0%
Negative
Sentence 2
POSITIVE
100%
Positive
0%
Neutral
0%
Negative
Sentence 3
POSITIVE
100%
Positive
0%
Neutral
0%
Negative
Sentence 4
POSITIVE
100%
Positive
0%
Neutral
0%
Negative
Sentence 5
POSITIVE
100%
Positive
0%
Neutral
0%
Negative
Sentence 6
NEUTRAL
0%
Positive
100%
Neutral
0%
Negative
Sentence 7
NEGATIVE
0%
Positive
0%
Neutral
100%
Negative
Sentence 8
POSITIVE
100%
Positive
0%
Neutral
0%
Negative
Named Entities: Contoso Steakhouse [Location]
midtown [Location-GPE]
NYC [Location-GPE]
last week [DateTime-DateRange]
dinner party [Event]
chief cook [PersonType]
owner [PersonType]
John Doe [Person]
kitchen [Location-Structural]
Sirloin steak [Product]
www.contososteakhouse.com [URL]
312-555-0176 [Phone Number]
order@contososteakhouse.com [Email]
food [Product]
PII Entities: Type: Organization
Value: Contoso

Type: DateTime
Value: last week

Type: PersonType
Value: chief cook

Type: PersonType
Value: owner

Type: Person
Value: John Doe

Type: URL
Value: www.contososteakhouse.com

Type: Phone Number
Value: 312-555-0176

Type: Email
Value: order@contososteakhouse.com

Type: Organization
Value: contososteakhouse

Linked Entities: We went to Contoso Steakhouse located at midtown NYC last week for a dinner party, and we adore the spot! They provide marvelous food and they have a great menu. The chief cook happens to be the owner (I think his name is John Doe) and he is super nice, coming out of the kitchen and greeted us all. We enjoyed very much dining in the place! The Sirloin steak I ordered was tender and juicy, and the place was impeccably clean. You can even pre-order from their online menu at www.contososteakhouse.com, call 312-555-0176 or send email to order@contososteakhouse.com! The only complaint I have is the food didn't come fast enough. Overall I highly recommend it!
{
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      {
        "id": "8b5581e2-4761-4177-85f8-9ec386c0753d",
        "detectedLanguage": {
          "name": "English",
          "iso6391Name": "en",
          "confidenceScore": 0.99
        }
      }
    ],
    "errors": [],
    "modelversion": "2021-01-05"
  },
  "keyPhrases": {
    "documents": [
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        "id": "8b5581e2-4761-4177-85f8-9ec386c0753d",
        "keyPhrases": [
          "The Sirloin steak",
          "Contoso Steakhouse",
          "midtown NYC",
          "dinner party",
          "great menu",
          "chief cook",
          "John Doe",
          "online menu",
          "marvelous food",
          "spot",
          "owner",
          "name",
          "kitchen",
          "dining",
          "place",
          "order",
          "contososteakhouse",
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          "complaint"
        ]
      }
    ],
    "errors": [],
    "modelversion": "2021-06-01"
  },
  "sentiment": {
    "documents": [
      {
        "id": "8b5581e2-4761-4177-85f8-9ec386c0753d",
        "sentiment": "mixed",
        "confidenceScores": {
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          "neutral": 0.0,
          "negative": 0.14
        },
        "sentences": [
          {
            "sentiment": "positive",
            "confidenceScores": {
              "positive": 0.99,
              "neutral": 0.01,
              "negative": 0.0
            },
            "offset": 0,
            "length": 105
          },
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            "sentiment": "positive",
            "confidenceScores": {
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            "offset": 106,
            "length": 55
          },
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            "offset": 300,
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          {
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            "sentiment": "neutral",
            "confidenceScores": {
              "positive": 0.0,
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            },
            "offset": 428,
            "length": 139
          },
          {
            "sentiment": "negative",
            "confidenceScores": {
              "positive": 0.0,
              "neutral": 0.0,
              "negative": 1.0
            },
            "offset": 568,
            "length": 62
          },
          {
            "sentiment": "positive",
            "confidenceScores": {
              "positive": 1.0,
              "neutral": 0.0,
              "negative": 0.0
            },
            "offset": 631,
            "length": 30
          }
        ]
      }
    ],
    "errors": [],
    "modelversion": "2020-04-01"
  },
  "entities": {
    "documents": [
      {
        "id": "8b5581e2-4761-4177-85f8-9ec386c0753d",
        "entities": [
          {
            "text": "Contoso Steakhouse",
            "category": "Location",
            "subcategory": null,
            "offset": 11,
            "length": 18,
            "confidencescore": 0.78
          },
          {
            "text": "midtown",
            "category": "Location",
            "subcategory": "GPE",
            "offset": 41,
            "length": 7,
            "confidencescore": 0.63
          },
          {
            "text": "NYC",
            "category": "Location",
            "subcategory": "GPE",
            "offset": 49,
            "length": 3,
            "confidencescore": 0.81
          },
          {
            "text": "last week",
            "category": "DateTime",
            "subcategory": "DateRange",
            "offset": 53,
            "length": 9,
            "confidencescore": 0.8
          },
          {
            "text": "dinner party",
            "category": "Event",
            "subcategory": null,
            "offset": 69,
            "length": 12,
            "confidencescore": 0.93
          },
          {
            "text": "chief cook",
            "category": "PersonType",
            "subcategory": null,
            "offset": 166,
            "length": 10,
            "confidencescore": 0.88
          },
          {
            "text": "owner",
            "category": "PersonType",
            "subcategory": null,
            "offset": 195,
            "length": 5,
            "confidencescore": 0.98
          },
          {
            "text": "John Doe",
            "category": "Person",
            "subcategory": null,
            "offset": 222,
            "length": 8,
            "confidencescore": 1.0
          },
          {
            "text": "kitchen",
            "category": "Location",
            "subcategory": "Structural",
            "offset": 272,
            "length": 7,
            "confidencescore": 0.95
          },
          {
            "text": "Sirloin steak",
            "category": "Product",
            "subcategory": null,
            "offset": 346,
            "length": 13,
            "confidencescore": 0.9
          },
          {
            "text": "www.contososteakhouse.com",
            "category": "URL",
            "subcategory": null,
            "offset": 477,
            "length": 25,
            "confidencescore": 0.8
          },
          {
            "text": "312-555-0176",
            "category": "Phone Number",
            "subcategory": null,
            "offset": 509,
            "length": 12,
            "confidencescore": 0.8
          },
          {
            "text": "order@contososteakhouse.com",
            "category": "Email",
            "subcategory": null,
            "offset": 539,
            "length": 27,
            "confidencescore": 0.8
          },
          {
            "text": "food",
            "category": "Product",
            "subcategory": null,
            "offset": 601,
            "length": 4,
            "confidencescore": 0.68
          }
        ]
      }
    ],
    "errors": [],
    "modelversion": "2021-06-01"
  },
  "entityLinking": {
    "documents": [
      {
        "id": "8b5581e2-4761-4177-85f8-9ec386c0753d",
        "entities": [
          {
            "name": "Steakhouse",
            "matches": [
              {
                "text": "Steakhouse",
                "offset": 19,
                "length": 10,
                "score": 0.0
              }
            ],
            "language": "en",
            "id": "Steakhouse",
            "url": "https://en.wikipedia.org/wiki/Steakhouse",
            "datasource": "Wikipedia"
          },
          {
            "name": "New York City",
            "matches": [
              {
                "text": "NYC",
                "offset": 49,
                "length": 3,
                "score": 0.0
              }
            ],
            "language": "en",
            "id": "New York City",
            "url": "https://en.wikipedia.org/wiki/New_York_City",
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          },
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          },
          {
            "name": "Sirloin steak",
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              {
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                "score": 0.0
              }
            ],
            "language": "en",
            "id": "Sirloin steak",
            "url": "https://en.wikipedia.org/wiki/Sirloin_steak",
            "datasource": "Wikipedia"
          }
        ]
      }
    ],
    "errors": [],
    "modelversion": "2021-06-01"
  },
  "entityPII": {
    "documents": [
      {
        "id": "8b5581e2-4761-4177-85f8-9ec386c0753d",
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          {
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            "category": "Organization",
            "subcategory": null,
            "offset": 11,
            "length": "7",
            "confidencescore": 0.58
          },
          {
            "text": "last week",
            "category": "DateTime",
            "subcategory": "DateRange",
            "offset": 53,
            "length": "9",
            "confidencescore": 0.8
          },
          {
            "text": "chief cook",
            "category": "PersonType",
            "subcategory": null,
            "offset": 166,
            "length": "10",
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          },
          {
            "text": "owner",
            "category": "PersonType",
            "subcategory": null,
            "offset": 195,
            "length": "5",
            "confidencescore": 0.93
          },
          {
            "text": "John Doe",
            "category": "Person",
            "subcategory": null,
            "offset": 222,
            "length": "8",
            "confidencescore": 0.98
          },
          {
            "text": "www.contososteakhouse.com",
            "category": "URL",
            "subcategory": null,
            "offset": 477,
            "length": "25",
            "confidencescore": 0.8
          },
          {
            "text": "312-555-0176",
            "category": "Phone Number",
            "subcategory": null,
            "offset": 509,
            "length": "12",
            "confidencescore": 0.8
          },
          {
            "text": "order@contososteakhouse.com",
            "category": "Email",
            "subcategory": null,
            "offset": 539,
            "length": "27",
            "confidencescore": 0.8
          },
          {
            "text": "contososteakhouse",
            "category": "Organization",
            "subcategory": null,
            "offset": 545,
            "length": "17",
            "confidencescore": 0.45
          }
        ]
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    ],
    "errors": [],
    "modelversion": "2021-01-15"
  }
}

Identify and categorize important concepts

Extract a broad range of prebuilt entities such as people, places, organizations, dates/times, numerals, and over 100 types of personally identifiable information (PII), including protected health information (PHI), in documents using named entity recognition.

Identify the main points in unstructured text

Quickly evaluate and identify the main points in unstructured text. Get a list of relevant phrases that best describe a passage using key phrase extraction. Or identify sentences that best convey the main idea of a document with extractive summarization (preview).

Better understand customer perception

Analyze positive and negative sentiment in social media, customer reviews, and other sources to get a pulse on your brand. Use opinion mining to explore customers' perception of specific attributes of products or services in text.

Process unstructured medical data

Extract insights from unstructured clinical documents such as doctors' notes, electronic health records, and patient intake forms using the health feature of Text Analytics. Recognize, classify, and determine relationships between medical concepts such as diagnosis, symptoms, and dosage and frequency of medication.

Create a conversational layer over your data

Get answers to questions from semi-structured and unstructured content such as URLs, FAQ, product manuals, blogs, support documents, and more.

Deploy anywhere, in the cloud or at the edge

Run Text Analytics wherever your data resides. Build applications that are optimized for both robust cloud capabilities and edge locality using containers.

Comprehensive privacy and security

  • Your data stays yours. Microsoft doesn't use the training performed on your text to improve models.
  • Choose where Cognitive Services processes your data with containers.
  • Backed by Azure infrastructure, Text Analytics offers enterprise-grade security, availability, compliance, and manageability.

Get the power, control, and customization you need with flexible pricing

  • Pay as you go based on the number of transactions, with no upfront costs.

Text Analytics resources and documentation

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Trusted by companies of all sizes

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IHC empowers service engineers

Royal IHC uses Azure Cognitive Search and Text Analytics to relieve its engineers from time-consuming manual data searches across disparate sources and give them insights on their structured and unstructured data.

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LaLiga is engaging millions of fans around the world with a personal digital assistant, using Text Analytics to process incoming queries and determine user intent in multiple languages.

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TIBCO brings root cause analysis to the edge

TIBCO is using Text Analytics and Anomaly Detector to detect and analyze anomalies such as sudden changes in data patterns, discover root causes, and provide suggested actions.

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Kotak Mahindra Bank accelerates productivity

Kotak Asset Management is transforming customer service management by enabling chatbots to easily analyze subject line, customer information, and email content to identify sentiment and trigger the next best action.

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Frequently asked questions about Text Analytics

  • Text Analytics detects a wide range of languages, variants, and dialects. See the language support documentation for more information.
  • Yes. Sentiment analysis and key phrase extraction are available for a select number of languages, and you may request additional languages in the Text Analytics Forum.
  • Key phrase extraction eliminates nonessential words and standalone adjectives. Adjective-noun combinations, such as "spectacular views" or "foggy weather," are returned together. Generally, output consists of nouns and objects of the sentence, and is listed in order of importance. Importance is measured by the number of times a particular concept is mentioned, or the relation of that element to other elements in the text.
  • Improvements to models and algorithms are announced if the change is major, and added to the service if the update is minor. Over time, you might find that the same text input results in a different sentiment score or key phrase output. This is a normal and intentional consequence of using managed machine learning resources in the cloud.
  • Yes, you can use the analyze operation in preview to combine more than one Text Analytics feature in the same asynchronous call. The analyze operation is currently only available in the Standard pricing tier and follows the same pricing criteria.

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