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edsnlp.pipelines.ner.scores.emergency.gemsa.factory

DEFAULT_CONFIG = dict(regex=patterns.regex, after_extract=patterns.after_extract, score_normalization=patterns.score_normalization_str, attr='NORM', window=20, verbose=0, ignore_excluded=False) module-attribute

create_component(nlp, name, regex, after_extract, score_normalization, attr, window, verbose, ignore_excluded)

Source code in edsnlp/pipelines/ner/scores/emergency/gemsa/factory.py 
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@deprecated_factory(
    "emergency.gemsa", "eds.emergency.gemsa", default_config=DEFAULT_CONFIG
)
@Language.factory("eds.emergency.gemsa", default_config=DEFAULT_CONFIG)
def create_component(
    nlp: Language,
    name: str,
    regex: List[str],
    after_extract: str,
    score_normalization: Union[str, Callable[[Union[str, None]], Any]],
    attr: str,
    window: int,
    verbose: int,
    ignore_excluded: bool,
):
    return Score(
        nlp,
        score_name=name,
        regex=regex,
        after_extract=after_extract,
        score_normalization=score_normalization,
        attr=attr,
        window=window,
        verbose=verbose,
        ignore_excluded=ignore_excluded,
    )