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edsnlp.pipelines.ner.scores.emergency.ccmu.factory

create_component(nlp, name='eds.emergency.ccmu', regex=patterns.regex, value_extract=patterns.value_extract, score_normalization=patterns.score_normalization_str, attr='NORM', window=20, ignore_excluded=False, ignore_space_tokens=False, flags=0)

Matcher for the Emergency CCMU score.

PARAMETER DESCRIPTION
nlp

The spaCy Language object

TYPE: Language

name

The name of the component

TYPE: str DEFAULT: 'eds.emergency.ccmu'

regex

The regex patterns to match

TYPE: List[str] DEFAULT: patterns.regex

value_extract

The regex pattern to extract the value from the matched text

TYPE: str DEFAULT: patterns.value_extract

score_normalization

The normalization function to apply to the extracted value

TYPE: Union[str, Callable[[Union[str, None]], Any]] DEFAULT: patterns.score_normalization_str

attr

The token attribute to match on (e.g. "TEXT" or "NORM")

TYPE: str DEFAULT: 'NORM'

window

The window size to search for the regex pattern

TYPE: int DEFAULT: 20

ignore_excluded

Whether to ignore excluded tokens

TYPE: bool DEFAULT: False

ignore_space_tokens

Whether to ignore space tokens

TYPE: bool DEFAULT: False

flags

The regex flags to use

TYPE: Union[re.RegexFlag, int] DEFAULT: 0

RETURNS DESCRIPTION
Score
Source code in edsnlp/pipelines/ner/scores/emergency/ccmu/factory.py 
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@deprecated_factory(
    "emergency.ccmu",
    "eds.emergency.ccmu",
    default_config=DEFAULT_CONFIG,
    assigns=["doc.ents", "doc.spans"],
)
@Language.factory(
    "eds.emergency.ccmu",
    default_config=DEFAULT_CONFIG,
    assigns=["doc.ents", "doc.spans"],
)
def create_component(
    nlp: Language,
    name: str = "eds.emergency.ccmu",
    regex: List[str] = patterns.regex,
    value_extract: str = patterns.value_extract,
    score_normalization: Union[
        str, Callable[[Union[str, None]], Any]
    ] = patterns.score_normalization_str,
    attr: str = "NORM",
    window: int = 20,
    ignore_excluded: bool = False,
    ignore_space_tokens: bool = False,
    flags: Union[re.RegexFlag, int] = 0,
):
    """
    Matcher for the Emergency CCMU score.

    Parameters
    ----------
    nlp: Language
        The spaCy Language object
    name: str
        The name of the component
    regex: List[str]
        The regex patterns to match
    value_extract: str
        The regex pattern to extract the value from the matched text
    score_normalization: Union[str, Callable[[Union[str, None]], Any]]
        The normalization function to apply to the extracted value
    attr: str
        The token attribute to match on (e.g. "TEXT" or "NORM")
    window: int
        The window size to search for the regex pattern
    ignore_excluded: bool
        Whether to ignore excluded tokens
    ignore_space_tokens: bool
        Whether to ignore space tokens
    flags: Union[re.RegexFlag, int]
        The regex flags to use

    Returns
    -------
    Score
    """
    return Score(
        nlp,
        score_name=name,
        regex=regex,
        value_extract=value_extract,
        score_normalization=score_normalization,
        attr=attr,
        window=window,
        ignore_excluded=ignore_excluded,
        ignore_space_tokens=ignore_space_tokens,
        flags=flags,
    )