TextContents[text]

gives a dataset of information about entities, dates, quantities and other content-related elements found in text.

TextContents[text,form]

searches for cases of the type form.

TextContents[text,{form1,form2,}]

searches for cases of types form1, form2,

TextContents[text,forms,props]

includes the property props for each object in the dataset produced.

Details and Options

  • In TextContents[text,], text can be a string, a file with plain text represented by File[], a ContentObject expression or a list of these text objects.
  • TextContents[{text1,text2,},] gives cases for each texti.
  • Identification type form can be:
  • "type"any text content type (e.g. "Noun", "City")
    Entity[,]a specific entity of a text content type
    form1|form2|
  • form matching any of the formi
  • Containing[outer,inner]forms of type outer containing type inner
    Verbatim["string"]a specific string to be matched exactly
    patterna string pattern to be matched
    Automaticentities, dates, quantities and other content-related elements
  • Possible choices for the property prop include:
  • "String"string of the identified text (default)
    "Position"start and end position of the string in text
    "Probability"estimated probability that the identification is correct
    "Type"type of content (entity type, )
    "Interpretation"standard interpretation of the identified string
    "Snippet"a snippet around the identified string
    "HighlightedSnippet"a snippet with the identified string highlighted
    Allall the preceding properties
    {prop1,prop2,}a list of property specifications
  • The following options can be given:
  • AcceptanceThresholdAutomaticminimum probability to accept identification
    TargetDevice"CPU"whether CPU or GPU computation should be used for entity detection
    VerifyInterpretationFalsewhether interpretability should be verified

Examples

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Basic Examples  (1)

Find entities in a text:

Only get the results for locations:

Only get the results for locations and quantities:

Get interpretations for all cases:

Get a specified set of properties for entities:

Options  (2)

AcceptanceThreshold  (1)

By default, all the detected entities have an estimated probability higher than 0.5:

Get only the entities that are highly probable to be correct by setting a high AcceptanceThreshold:

VerifyInterpretation  (1)

By default, some entities cannot be interpreted, either because they are not correct or because they are not yet in the knowledgebase:

Use VerifyInterpretation to filter out the entities that cannot be interpreted:

Properties & Relations  (1)

TextContents handles the same types as TextPosition and TextCases and always identifies the same substrings as these functions for a given type:

A dataset that is similar to the output of TextContents can be obtained using TextCases:

Neat Examples  (1)

Load the text of a Wikipedia page about the Moon:

Extract notable text contents from the page:

Visualize the frequency of content types found on the page:

Find potential notable persons identified on the page:

Interpret these persons as entities:

Visualize occupations of these persons:

Introduced in 2019
 (12.0)