CLAMS wrapper for spaCy NLP (v2.2)

About this version

About this app (See raw metadata.json)

Apply spaCy NLP to all text documents in a MMIF file.

Inputs

(Note: “*” as a property value means that the property is required but can be any value.)

Configurable Parameters

(Note: Multivalued means the parameter can have one or more values.)

  • pretokenized: optional, defaults to false

    • Type: boolean
    • Multivalued: False
    • Choices: false, true

    Boolean parameter to set the app to use existing tokenization, if available, for text documents for NLP processing. Useful to process ASR documents, for example.

  • pretty: optional, defaults to false

    • Type: boolean
    • Multivalued: False
    • Choices: false, true

    The JSON body of the HTTP response will be re-formatted with 2-space indentation

  • runningTime: optional, defaults to true

    • Type: boolean
    • Multivalued: False
    • Choices: false, true

    The running time of the app will be recorded in the view metadata

  • hwFetch: optional, defaults to false

    • Type: boolean
    • Multivalued: False
    • Choices: false, true

    The hardware information (architecture, GPU and vRAM) will be recorded in the view metadata

  • tfSamplingMode: optional, defaults to representatives

    • Type: string
    • Multivalued: False
    • Choices: representatives, single, all

    Sampling mode for TimeFrame annotations. Has no effect when the app does not process TimeFrames. “representatives” uses all representative timepoints if present, otherwise skips the TimeFrame. “single” uses the middle representative if present, otherwise extracts an image from the midpoint of the start/end interval (midpoint is calculated by floor division of the sum of start and end). “all” uses all target timepoints if present, otherwise extracts all images from the time interval.

Outputs

(Note: “*” as a property value means that the property is required but can be any value.)

(Note: Not all output annotations are always generated.)