medkit.text.spacy

Submodules

• medkit.text.spacy.displacy_utils
• medkit.text.spacy.doc_pipeline
• medkit.text.spacy.edsnlp
• medkit.text.spacy.pipeline
• medkit.text.spacy.spacy_utils

Classes

SpacyDocPipeline	DocPipeline to obtain annotations created using spacy.
SpacyPipeline	Segment annotator relying on a Spacy pipeline.

Package Contents

class medkit.text.spacy.SpacyDocPipeline(nlp: spacy.Language, medkit_labels_anns: list[str] | None = None, medkit_attrs: list[str] | None = None, spacy_entities: list[str] | None = None, spacy_span_groups: list[str] | None = None, spacy_attrs: list[str] | None = None, medkit_attribute_factories: dict[str, Callable[[spacy.tokens.Span, str], medkit.core.Attribute]] | None = None, name: str | None = None, uid: str | None = None)

Bases: medkit.core.DocOperation

DocPipeline to obtain annotations created using spacy.

init_args

nlp

medkit_labels_anns

medkit_attrs

spacy_entities

spacy_span_groups

spacy_attrs

medkit_attribute_factories

run(medkit_docs: list[medkit.core.text.TextDocument]) → None

Run a spacy pipeline on a list of medkit documents.

Each medkit document is converted to spacy document (Doc object), with the selected annotations and attributes. Then, the spacy pipeline is executed and finally, the new annotations and attributes are converted into medkit annotations.

Parameters:

medkit_docslist of TextDocument

List of TextDocuments on which to run the pipeline

class medkit.text.spacy.SpacyPipeline(nlp: spacy.Language, spacy_entities: list[str] | None = None, spacy_span_groups: list[str] | None = None, spacy_attrs: list[str] | None = None, medkit_attribute_factories: dict[str, Callable[[spacy.tokens.Span, str], medkit.core.Attribute]] | None = None, name: str | None = None, uid: str | None = None)

Bases: medkit.core.operation.Operation

Segment annotator relying on a Spacy pipeline.

init_args

nlp

spacy_entities

spacy_span_groups

spacy_attrs

medkit_attribute_factories

run(segments: list[medkit.core.text.Segment]) → list[medkit.core.text.Segment]

Run the operation.

Run a spacy pipeline on a list of segments provided as input and returns a new list of segments. Each segment is converted to spacy document (Doc object). Then, the spacy pipeline is executed and finally, the new annotations and attributes are converted into medkit annotations.

Parameters:

segmentslist of Segment

List of segments on which to run the spacy pipeline

Returns:

list of Segment

List of new annotations

_find_segments_in_spacy_doc(spacy_doc: spacy.tokens.Doc, medkit_source_ann: medkit.core.text.Segment)