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NER (named entity recognition) is a subtask where entities that appear in the content are identified and output with their determined category. ELSA (entity level sentiment analysis) is also part of the NER output. The relating fields (sentimentValue, sentimentScore) are included below value in the response and provides the sentiment in which the specific entity was mentioned.

Note: Clients must reach out to their Account Manager for access to NER and ELSA.

Syntax

"ner": [
      {
      "value": "<Identified Entity>",
      "sentimentValue": "<Positive, Neutral or Negative>",
      "sentimentScore": <-1 - 1> 
      "type": "<IAB v3.0 category Name>"
    }
  ]
}

Example

"ner": [
      {
        "value": "vegas",
        "sentimentValue": "neutral",
        "sentimentScore": 0.296,
        "type": "location"
      },
      {
        "value": "us",
        "sentimentValue": "neutral",
        "sentimentScore": 0,
        "type": "location"
      },
      {
        "value": "fanatics",
        "sentimentValue": "neutral",
        "sentimentScore": 0,
        "type": "organization"
      },
      {
        "value": "patriots",
        "sentimentValue": "neutral",
        "sentimentScore": 0,
        "type": "organization"
      },
      {
        "value": "keisha epps",
        "sentimentValue": "neutral",
        "sentimentScore": 0,
        "type": "person"
      },
      {
        "value": "matt barnes",
        "sentimentValue": "neutral",
        "sentimentScore": 0,
        "type": "person"
      },
      {
        "value": "jumanji",
        "sentimentValue": "negative",
        "sentimentScore": -0.4767,
        "type": "miscellaneous"
      }
    ],

Languages

All supported languages.

Data Type

Array of objects

More Information

IAB Tech Lab Content Taxonomy ID - V3

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