Key Phrase Extraction cognitive skill

  • Article

The Key Phrase Extraction skill evaluates unstructured text, and for each record, returns a list of key phrases. This skill uses the Key Phrase machine learning models provided by Azure AI Language.

This capability is useful if you need to quickly identify the main talking points in the record. For example, given input text "The food was delicious and there were wonderful staff", the service returns "food" and "wonderful staff".

Note

This skill is bound to Azure AI services and requires a billable resource for transactions that exceed 20 documents per indexer per day. Execution of built-in skills is charged at the existing Azure AI services Standard Pay-in-Advance Offer price.

@odata.type

Microsoft.Skills.Text.KeyPhraseExtractionSkill

Data limits

The maximum size of a record should be 50,000 characters as measured by String.Length. If you need to break up your data before sending it to the key phrase extractor, consider using the Text Split skill. If you do use a text split skill, set the page length to 5000 for the best performance.

Skill parameters

Parameters are case-sensitive.

Inputs Description
defaultLanguageCode (Optional) The language code to apply to documents that don't specify language explicitly. If the default language code isn't specified, English (en) is used as the default language code.
See the full list of supported languages.
maxKeyPhraseCount (Optional) The maximum number of key phrases to produce.
modelVersion (Optional) Specifies the version of the model to use when calling the key phrase API. It defaults to the latest available when not specified. We recommend you don't specify this value unless it's necessary.

Skill inputs

Input Description
text The text to be analyzed.
languageCode A string indicating the language of the records. If this parameter isn't specified, the default language code is used to analyze the records.
See the full list of supported languages.

Skill outputs

Output Description
keyPhrases A list of key phrases extracted from the input text. The key phrases are returned in order of importance.

Sample definition

Consider a SQL record that has the following fields:

{
    "content": "Glaciers are huge rivers of ice that ooze their way over land, powered by gravity and their own sheer weight. They accumulate ice from snowfall and lose it through melting. As global temperatures have risen, many of the world's glaciers have already started to shrink and retreat. Continued warming could see many iconic landscapes - from the Canadian Rockies to the Mount Everest region of the Himalayas - lose almost all their glaciers by the end of the century.",
    "language": "en"
}

Then your skill definition might look like this:

 {
    "@odata.type": "#Microsoft.Skills.Text.KeyPhraseExtractionSkill",
    "inputs": [
      {
        "name": "text",
        "source": "/document/content"
      },
      {
        "name": "languageCode",
        "source": "/document/language" 
      }
    ],
    "outputs": [
      {
        "name": "keyPhrases",
        "targetName": "myKeyPhrases"
      }
    ]
  }

Sample output

For the previous example, the output of your skill is written to a new node in the enriched tree called "document/myKeyPhrases" since that is the targetName that we specified. If you don't specify a targetName, then it would be "document/keyPhrases".

document/myKeyPhrases

[
  "world's glaciers", 
  "huge rivers of ice", 
  "Canadian Rockies", 
  "iconic landscapes",
  "Mount Everest region",
  "Continued warming"
]

You can use "document/myKeyPhrases" as input into other skills, or as a source of an output field mapping.

Warnings

If you provide an unsupported language code, a warning is generated and key phrases aren't extracted. If your text is empty, a warning is produced. If your text is larger than 50,000 characters, only the first 50,000 characters are analyzed and a warning is issued.

See also