Python matcher.Matcher方法代碼示例

本文整理匯總了Python中spacy.matcher.Matcher方法的典型用法代碼示例。如果您正苦於以下問題：Python matcher.Matcher方法的具體用法？Python matcher.Matcher怎麽用？Python matcher.Matcher使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類spacy.matcher的用法示例。

在下文中一共展示了matcher.Matcher方法的14個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。

示例1: init

# 需要導入模塊: from spacy import matcher [as 別名]
# 或者: from spacy.matcher import Matcher [as 別名]
def __init__(self, resume):
        nlp = spacy.load('en_core_web_sm')
        self.__matcher = Matcher(nlp.vocab)
        self.__details = {
            'name'              : None,
            'email'             : None,
            'mobile_number'     : None,
            'skills'            : None,
            'education'         : None,
            'experience'        : None,
            'competencies'      : None,
            'measurable_results': None
        }
        self.__resume      = resume
        self.__text_raw    = utils.extract_text(self.__resume, os.path.splitext(self.__resume)[1])
        self.__text        = ' '.join(self.__text_raw.split())
        self.__nlp         = nlp(self.__text)
        self.__noun_chunks = list(self.__nlp.noun_chunks)
        self.__get_basic_details()

開發者ID:OmkarPathak，項目名稱:ResumeParser，代碼行數:21，代碼來源:resume_parser.py

示例2: init

# 需要導入模塊: from spacy import matcher [as 別名]
# 或者: from spacy.matcher import Matcher [as 別名]
def __init__(self, spacy_pipeline):
        self.nlp = spacy_pipeline
        Token.set_extension('feature_is_time_unit', default=False)
        self.nlp.entity.add_label('time_unit')
        self.time_matcher = Matcher(self.nlp.vocab)

        self.time_matcher.add('UNIT_OF_TIME', None,
                              [{'LOWER': 'sec'}],
                              [{'LOWER': 'second'}],
                              [{'LOWER': 'seconds'}],
                              [{'LOWER': 'min'}],
                              [{'LOWER': 'minute'}],
                              [{'LOWER': 'minutes'}],
                              [{'LOWER': 'hr'}],
                              [{'LOWER': 'hour'}],
                              [{'LOWER': 'day'}],
                              [{'LOWER': 'days'}],
                              [{'LOWER': 'week'}],
                              [{'LOWER': 'weeks'}],
                              [{'LOWER': 'month'}],
                              [{'LOWER': 'months'}],
                              [{'LOWER': 'year'}],
                              [{'LOWER': 'years'}],
                              [{'LOWER': 'yrs'}]
                              )

開發者ID:NLPatVCU，項目名稱:medaCy，代碼行數:27，代碼來源:time_unit_component.py

示例3: init

# 需要導入模塊: from spacy import matcher [as 別名]
# 或者: from spacy.matcher import Matcher [as 別名]
def __init__(self, spacy_pipeline):
        self.nlp = spacy_pipeline
        Token.set_extension('feature_is_frequency_indicator', default=False)
        self.nlp.entity.add_label('frequency_indicator')
        self.frequency_matcher = Matcher(self.nlp.vocab)

        self.frequency_matcher.add('FREQUENCY_MATCHER', None,
                               [{'LOWER': 'bid'}],
                               [{'LOWER': 'prn'}],
                               [{'LOWER': 'qid'}],
                               [{'LOWER': 'tid'}],
                               [{'LOWER': 'qd'}],
                               [{'LOWER': 'daily'}],
                               [{'LOWER': 'hs'}],
                               [{'LOWER': 'as'}, {'LOWER': 'needed'}],
                               [{'LOWER': 'once'}, {'LOWER': 'a'}, {'LOWER': 'day'}],
                               [{'LOWER': 'twice'}, {'LOWER': 'a'}, {'LOWER': 'day'}]
                               )

開發者ID:NLPatVCU，項目名稱:medaCy，代碼行數:20，代碼來源:frequency_unit_component.py

示例4: init

# 需要導入模塊: from spacy import matcher [as 別名]
# 或者: from spacy.matcher import Matcher [as 別名]
def __init__(self, spacy_model: str = 'en_core_web_sm', disable: Optional[Iterable[str]] = None, **kwargs):
        if disable is None:
            disable = ['parser', 'ner']

        self.model = _try_load_spacy_model(spacy_model, disable=disable)

        below = lambda text: bool(re.compile(r'below|cheap').match(text))
        BELOW = self.model.vocab.add_flag(below)

        above = lambda text: bool(re.compile(r'above|start').match(text))
        ABOVE = self.model.vocab.add_flag(above)

        self.matcher = Matcher(self.model.vocab)

        self.matcher.add('below', None, [{BELOW: True}, {'LOWER': 'than', 'OP': '?'},
                                         {'LOWER': 'from', 'OP': '?'}, {'ORTH': '$', 'OP': '?'},
                                         {'ENT_TYPE': 'MONEY', 'LIKE_NUM': True}])

        self.matcher.add('above', None, [{ABOVE: True}, {'LOWER': 'than', 'OP': '?'},
                                         {'LOWER': 'from', 'OP': '?'}, {'ORTH': '$', 'OP': '?'},
                                         {'ENT_TYPE': 'MONEY', 'LIKE_NUM': True}])

開發者ID:deepmipt，項目名稱:DeepPavlov，代碼行數:23，代碼來源:ecommerce_preprocess.py

示例5: init

# 需要導入模塊: from spacy import matcher [as 別名]
# 或者: from spacy.matcher import Matcher [as 別名]
def __init__(self, nlp, patterns: list = None):
        """
        SpaCy pipe to match Entity based on multiple patterns.

        Pattern examples:
        patterns = [
            {'kind': 'phrase', 'value': 'amazon', 'entity': 'PRODUCT'},
            {'kind': 'regex', 'value': 'ama(.+)', 'entity': 'PRODUCT'}
        ]

        :param nlp: The NLP object
        :param patterns: The matcher patterns
        """
        self.nlp = nlp
        self.phrase_matcher = PhraseMatcher(nlp.vocab)
        self.matcher = Matcher(nlp.vocab)

        self.extra_patterns = []
        # start add pattern
        self.add_patterns(patterns=patterns or [])

開發者ID:kororo，項目名稱:excelcy，代碼行數:22，代碼來源:pipe.py

示例6: init

# 需要導入模塊: from spacy import matcher [as 別名]
# 或者: from spacy.matcher import Matcher [as 別名]
def __init__(
        self,
        resume,
        skills_file=None,
        custom_regex=None
    ):
        nlp = spacy.load('en_core_web_sm')
        custom_nlp = spacy.load(os.path.dirname(os.path.abspath(__file__)))
        self.__skills_file = skills_file
        self.__custom_regex = custom_regex
        self.__matcher = Matcher(nlp.vocab)
        self.__details = {
            'name': None,
            'email': None,
            'mobile_number': None,
            'skills': None,
            'college_name': None,
            'degree': None,
            'designation': None,
            'experience': None,
            'company_names': None,
            'no_of_pages': None,
            'total_experience': None,
        }
        self.__resume = resume
        if not isinstance(self.__resume, io.BytesIO):
            ext = os.path.splitext(self.__resume)[1].split('.')[1]
        else:
            ext = self.__resume.name.split('.')[1]
        self.__text_raw = utils.extract_text(self.__resume, '.' + ext)
        self.__text = ' '.join(self.__text_raw.split())
        self.__nlp = nlp(self.__text)
        self.__custom_nlp = custom_nlp(self.__text_raw)
        self.__noun_chunks = list(self.__nlp.noun_chunks)
        self.__get_basic_details()

開發者ID:OmkarPathak，項目名稱:pyresparser，代碼行數:37，代碼來源:resume_parser.py

示例7: load_matcher

# 需要導入模塊: from spacy import matcher [as 別名]
# 或者: from spacy.matcher import Matcher [as 別名]
def load_matcher(nlp):
    config = configparser.ConfigParser()
    config.read("paths.cfg")
    with open(config["paths"]["matcher_patterns"], "r", encoding="utf8") as f:
        all_patterns = json.load(f)

    matcher = Matcher(nlp.vocab)
    for concept, pattern in tqdm(all_patterns.items(), desc="Adding patterns to Matcher."):
        matcher.add(concept, None, pattern)
    return matcher

開發者ID:INK-USC，項目名稱:KagNet，代碼行數:12，代碼來源:grounding_concepts.py

示例8: init

# 需要導入模塊: from spacy import matcher [as 別名]
# 或者: from spacy.matcher import Matcher [as 別名]
def __init__(self, spacy_pipeline):
        self.nlp = spacy_pipeline
        Token.set_extension('feature_is_measurement_unit', default=False)
        self.nlp.entity.add_label('measurement_unit')
        self.unit_of_measurement_matcher = Matcher(self.nlp.vocab)

        self.unit_of_measurement_matcher.add('UNIT_OF_MEASUREMENT', None,
                         [{'ENT_TYPE': 'mass_unit'}, {'ORTH': '/'}, {'ENT_TYPE': 'volume_unit'}],
                         [{'ENT_TYPE': 'volume_unit'}, {'ORTH': '/'}, {'ENT_TYPE': 'time_unit'}],
                         [{'ENT_TYPE': 'form_unit'}, {'ORTH': '/'}, {'ENT_TYPE': 'volume_unit'}]
                         )

開發者ID:NLPatVCU，項目名稱:medaCy，代碼行數:13，代碼來源:measurement_unit_component.py

示例9: init

# 需要導入模塊: from spacy import matcher [as 別名]
# 或者: from spacy.matcher import Matcher [as 別名]
def __init__(self, spacy_pipeline):
        self.nlp = spacy_pipeline
        Token.set_extension('feature_is_volume_unit', default=False)
        self.nlp.entity.add_label('volume_unit')
        self.volume_matcher = Matcher(self.nlp.vocab)

        self.volume_matcher.add('UNIT_OF_VOLUME', None,
                                [{'LOWER': 'ml'}],
                                 [{'ORTH': 'dL'}],
                                [{'LOWER': 'cc'}],
                                [{'ORTH': 'L'}])

開發者ID:NLPatVCU，項目名稱:medaCy，代碼行數:13，代碼來源:volume_unit_component.py

示例10: init

# 需要導入模塊: from spacy import matcher [as 別名]
# 或者: from spacy.matcher import Matcher [as 別名]
def __init__(self, spacy_pipeline):
        self.nlp = spacy_pipeline
        Token.set_extension('feature_is_mass_unit', default=False)
        self.nlp.entity.add_label('mass_unit')
        self.mass_matcher = Matcher(self.nlp.vocab)

        self.mass_matcher.add('UNIT_OF_MASS', None,
                              [{'LOWER': 'mcg'}],
                              [{'LOWER': 'microgram'}],
                              [{'LOWER': 'micrograms'}],
                              [{'ORTH': 'mg'}],
                              [{'LOWER': 'milligram'}],
                              [{'LOWER': 'g'}],
                              [{'LOWER': 'kg'}],
                              [{'ORTH': 'mEq'}])

開發者ID:NLPatVCU，項目名稱:medaCy，代碼行數:17，代碼來源:mass_unit_component.py

示例11: init

# 需要導入模塊: from spacy import matcher [as 別名]
# 或者: from spacy.matcher import Matcher [as 別名]
def __init__(self, vocab, boundary_protection_rules=[]):
        self.matcher = Matcher(vocab)
        for rule in boundary_protection_rules:
            self.matcher.add(rule["label"], None, rule["pattern"])

開發者ID:ICLRandD，項目名稱:Blackstone，代碼行數:6，代碼來源:sentence_segmenter.py

示例12: init

# 需要導入模塊: from spacy import matcher [as 別名]
# 或者: from spacy.matcher import Matcher [as 別名]
def __init__(self, nlp) -> None:
        Doc.set_extension("compound_cases", default=[], force=True)
        self.matcher = Matcher(nlp.vocab)
        common_pattern = [{"ent_type": "CASENAME"}, {"ent_type": "CITATION", "OP": "+"}]
        possessive_pattern = [
            {"ent_type": "CASENAME"},
            {"lower": "case"},
            {"ent_type": "CITATION"},
        ]
        self.matcher.add("compound_case", None, common_pattern, possessive_pattern)
        self.global_matcher = Matcher(nlp.vocab)
        merge_ents = nlp.create_pipe("merge_entities")
        nlp.add_pipe(merge_ents)

開發者ID:ICLRandD，項目名稱:Blackstone，代碼行數:15，代碼來源:compound_cases.py

示例13: init

# 需要導入模塊: from spacy import matcher [as 別名]
# 或者: from spacy.matcher import Matcher [as 別名]
def __init__(self, nlp) -> None:
        Doc.set_extension("abbreviations", default=[], force=True)
        Span.set_extension("long_form", default=None, force=True)

        self.matcher = Matcher(nlp.vocab)
        self.matcher.add(
            "parenthesis", None, [{"ORTH": "("}, {"OP": "+"}, {"ORTH": ")"}]
        )
        self.global_matcher = Matcher(nlp.vocab)

開發者ID:ICLRandD，項目名稱:Blackstone，代碼行數:11，代碼來源:abbreviations.py

示例14: add_pattern

# 需要導入模塊: from spacy import matcher [as 別名]
# 或者: from spacy.matcher import Matcher [as 別名]
def add_pattern(self, kind: str, value, entity: str):
        """
        Add pattern into matcher algorithm. There are two different types:
        - phrase: This uses PhraseMatcher which described in https://spacy.io/usage/linguistic-features#adding-phrase-patterns
        - regex: This uses Matcher which described in https://spacy.io/usage/linguistic-features#regex

        :param kind: Pattern matcher type, either 'phrase', 'regex'
        :param value: Entity pattern matcher
        :param entity: Entity to be matched
        """
        if kind == 'phrase':
            self.phrase_matcher.add(entity, None, *[self.nlp(value)])
        elif kind == 'regex':
            regex_flag = self.nlp.vocab.add_flag(lambda text: self.eval_regex(pattern=value, text=text))
            self.matcher.add(entity, None, [{regex_flag: True}])

開發者ID:kororo，項目名稱:excelcy，代碼行數:17，代碼來源:pipe.py

注：本文中的spacy.matcher.Matcher方法示例由純淨天空整理自Github/MSDocs等開源代碼及文檔管理平台，相關代碼片段篩選自各路編程大神貢獻的開源項目，源碼版權歸原作者所有，傳播和使用請參考對應項目的License；未經允許，請勿轉載。

示例1: __init__

示例2: __init__

示例3: __init__

示例4: __init__

示例5: __init__

示例6: __init__