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This is unreleased documentation for Rasa Open Source Documentation Main/Unreleased version.
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Version: Main/Unreleased

rasa.nlu.extractors.regex_entity_extractor

RegexEntityExtractor Objects

@DefaultV1Recipe.register(
DefaultV1Recipe.ComponentType.ENTITY_EXTRACTOR, is_trainable=True
)
class RegexEntityExtractor(GraphComponent, EntityExtractorMixin)

Extracts entities via lookup tables and regexes defined in the training data.

get_default_config

| @staticmethod
| get_default_config() -> Dict[Text, Any]

The component's default config (see parent class for full docstring).

create

| @classmethod
| create(cls, config: Dict[Text, Any], model_storage: ModelStorage, resource: Resource, execution_context: ExecutionContext) -> RegexEntityExtractor

Creates a new GraphComponent.

Arguments:

  • config - This config overrides the default_config.
  • model_storage - Storage which graph components can use to persist and load themselves.
  • resource - Resource locator for this component which can be used to persist and load itself from the model_storage.
  • execution_context - Information about the current graph run. Unused.
  • Returns - An instantiated GraphComponent.

__init__

| __init__(config: Dict[Text, Any], model_storage: ModelStorage, resource: Resource, patterns: Optional[List[Dict[Text, Text]]] = None) -> None

Creates a new instance.

Arguments:

  • config - The configuration.
  • model_storage - Storage which graph components can use to persist and load themselves.
  • resource - Resource locator for this component which can be used to persist and load itself from the model_storage.
  • patterns - a list of patterns

train

| train(training_data: TrainingData) -> Resource

Extract patterns from the training data.

Arguments:

  • training_data - the training data

process

| process(messages: List[Message]) -> List[Message]

Extracts entities from messages and appends them to the attribute.

If no patterns where found during training, then the given messages will not be modified. In particular, if no ENTITIES attribute exists yet, then it will not be created.

If no pattern can be found in the given message, then no entities will be added to any existing list of entities. However, if no ENTITIES attribute exists yet, then an ENTITIES attribute will be created.

Returns:

the given list of messages that have been modified

load

| @classmethod
| load(cls, config: Dict[Text, Any], model_storage: ModelStorage, resource: Resource, execution_context: ExecutionContext, **kwargs: Any, ,) -> RegexEntityExtractor

Loads trained component (see parent class for full docstring).

persist

| persist() -> None

Persist this model.