Skip to main content
Assigns each text to one or more categories. Each category is defined by a list of keywords a text must include or exclude to be labelled accordingly. In addition, each category may specify whether a keyword must be matched explicitly, ignoring its case (lower, upper) etc. See parameters below for further details.

Usage

The following example shows how the step can be used in a recipe.

Examples

The following defines the keywords to be included or exluded for each of three categories, labelled “journalist”, “business” and “CEO”. Note how in the case of “CEO” we’re looking for occurrences of the spelling with capitals only.

Inputs & Outputs

The following are the inputs expected by the step and the outputs it produces. These are generally columns (ds.first_name), datasets (ds or ds[["first_name", "last_name"]]) or models (referenced by name e.g. "churn-clf").
column[text|category]
required
A text column to label.
column[list[category]]
required
A column containing the labels assigned to each text.

Configuration

The following parameters can be used to configure the behaviour of the step by including them in a json object as the last “input” to the step, i.e. step(..., {"param": "value", ...}) -> (output).

Parameters

object
One or more named text categories. Each parameter should be a key indicating the name/label to show for a specific text category, and should have an object as value specifying the terms a text must or must not contain for that particular label to apply. Also see examples above.
array[string]
List of strings a text must include to apply a label.
string
Each item in array.
array[string]
List of strings a text must not include to apply a label.
string
Each item in array.
boolean
default:"false"
Whether to make search accent-sensitive.
boolean
default:"false"
Whether to make search case-sensitive.
boolean
default:"true"
Whether to match whole words only. If enabled, only matches a word if it is surrounded by non-alphanumeric characters.