edsnlp.pipelines.ner.drugs.factory

DEFAULT_CONFIG = dict(attr='NORM', ignore_excluded=False, term_matcher=TerminologyTermMatcher.exact, term_matcher_config={}) module-attribute

create_component(nlp, name, attr, ignore_excluded, term_matcher, term_matcher_config)

Source code in edsnlp/pipelines/ner/drugs/factory.py

@Language.factory(
    "eds.drugs",
    default_config=DEFAULT_CONFIG,
    assigns=["doc.ents", "doc.spans"],
)
def create_component(
    nlp: Language,
    name: str,
    attr: str,
    ignore_excluded: bool,
    term_matcher: TerminologyTermMatcher,
    term_matcher_config: Dict[str, Any],
):
    return TerminologyMatcher(
        nlp,
        label="drug",
        terms=patterns.get_patterns(),
        regex=dict(),
        attr=attr,
        ignore_excluded=ignore_excluded,
        term_matcher=term_matcher,
        term_matcher_config=term_matcher_config,
    )