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Version: Main/Unreleased
rasa.nlu.extractors.spacy_entity_extractor
SpacyEntityExtractor Objects
@DefaultV1Recipe.register(
DefaultV1Recipe.ComponentType.ENTITY_EXTRACTOR,
is_trainable=False,
model_from="SpacyNLP",
)
class SpacyEntityExtractor(GraphComponent, EntityExtractorMixin)
Entity extractor which uses SpaCy.
required_components
@classmethod
def required_components(cls) -> List[Type]
Components that should be included in the pipeline before this component.
get_default_config
@staticmethod
def get_default_config() -> Dict[Text, Any]
The component's default config (see parent class for full docstring).
__init__
def __init__(config: Dict[Text, Any]) -> None
Initialize SpacyEntityExtractor.
create
@classmethod
def create(cls, config: Dict[Text, Any], model_storage: ModelStorage,
resource: Resource,
execution_context: ExecutionContext) -> GraphComponent
Creates a new component (see parent class for full docstring).
required_packages
@staticmethod
def required_packages() -> List[Text]
Lists required dependencies (see parent class for full docstring).
process
def process(messages: List[Message], model: SpacyModel) -> List[Message]
Extract entities using SpaCy.
Arguments:
messages
- List of messages to process.model
- Container holding a loaded spacy nlp model.Returns
- The processed messages.