classifyAPI policy structure has two notable sections. First, the
modelsarray will have one item that is keyed by
csvand plain-text data formats are supported.
labelsarray is required to specify named entities to search for, including:
label_predictorsobject where you can define custom predictors that will create custom entity labels.
regex: Create your own regular expressions to match and yield custom labels. The value for this property should be an object that is keyed by the labels you wish to create. For each label you wish to create, you should provide an array of patterns. Patterns are objects consisting of:
score: One of high, med, low. These map to floating point values of .8, ,5 and .2 respectively. If omitted the default is high.
regex: The actual regex that will be used to match. When crafting your regex and testing it, ensure that it is compatible with Python 3.
use_nlp: trueto a classification model will enable entity predictions using natural language models.