classify
API policy structure has two notable sections. First, the models
array will have one item that is keyed by classify
.classify
object:data_source
is requiredcsv
and plain-text data formats are supported.labels
array is required to specify named entities to search for, including:label_predictors
object 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: true
to a classification model will enable entity predictions using natural language models.person_name
gretel/spacy.