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edsnlp.pipelines.ner.covid.factory

create_component(nlp, name='eds.covid', attr='LOWER', ignore_excluded=False, ignore_space_tokens=False)

Create a factory that returns new GenericMatcher with patterns for covid

PARAMETER DESCRIPTION
nlp

spaCy Language object.

TYPE: Language

name

The name of the pipe

TYPE: str DEFAULT: 'eds.covid'

attr

Attribute to match on, eg TEXT, NORM, etc.

TYPE: Union[str, Dict[str, str]] DEFAULT: 'LOWER'

ignore_excluded

Whether to skip excluded tokens during matching.

TYPE: bool DEFAULT: False

ignore_space_tokens

Whether to skip space tokens during matching.

TYPE: bool DEFAULT: False

RETURNS DESCRIPTION
GenericMatcher
Source code in edsnlp/pipelines/ner/covid/factory.py 
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@Language.factory(
    "eds.covid",
    default_config=DEFAULT_CONFIG,
    assigns=["doc.ents", "doc.spans"],
)
def create_component(
    nlp: Language,
    name: str = "eds.covid",
    attr: Union[str, Dict[str, str]] = "LOWER",
    ignore_excluded: bool = False,
    ignore_space_tokens: bool = False,
):
    """
    Create a factory that returns new GenericMatcher with patterns for covid

    Parameters
    ----------
    nlp: Language
        spaCy `Language` object.
    name: str
        The name of the pipe
    attr: Union[str, Dict[str, str]]
        Attribute to match on, eg `TEXT`, `NORM`, etc.
    ignore_excluded: bool
        Whether to skip excluded tokens during matching.
    ignore_space_tokens: bool
        Whether to skip space tokens during matching.

    Returns
    -------
    GenericMatcher
    """

    return GenericMatcher(
        nlp,
        terms=None,
        regex=dict(covid=patterns.pattern),
        attr=attr,
        ignore_excluded=ignore_excluded,
        ignore_space_tokens=ignore_space_tokens,
    )