label_texts_containing_from_query
Label texts given an elastic-like query string.
Given a query of the form “word1; word2 OR word3”, texts containing “word1” will be labeled as
“word1”, and texts containing “word2” or “word3” will be labeled as “word2 OR word3”. In other words, each semicolon-separated
string acts as both query and corresponding label. Texts matching multiple queries will be assigned multiple labels.
Usage
The following example shows how the step can be used in a recipe.Examples
Examples
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").
Inputs
Inputs
A text column to label.
Outputs
Outputs
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
Parameters
Query to label.
Query is a string of labels/categories and associated keywords (see examples below).
Use ”;” to separate categories, “OR” to join words for a category, and ”-” to exclude words from a category.
The category label(s) will be formed using the query, e.g. a text containing “AA” and “BB” will be tagged as [AA,BB].
Examples
Examples
- Cristiano OR -Five; for
Whether to make search accent sensitive.
Whether to make search case sensitive.
Whether to match whole words only.
If enabled, only matches a word if it is surrounded by non-alphanumeric characters.
Whether to return only the first match.
If True, only the first match will be assigned to each text. The result will be a simple categorical column.
If False, all identified matches will be assigned to each text. The result will be a multivalued column containing lists of categories.