def __call__(self, document, sentences_count):
        ratings = defaultdict(int)

        if self._cue_weight > 0.0:
            method = self._build_cue_method_instance()
            ratings = self._update_ratings(ratings, method.rate_sentences(document))
        if self._key_weight > 0.0:
            method = self._build_key_method_instance()
            ratings = self._update_ratings(ratings, method.rate_sentences(document))
        if self._title_weight > 0.0:
            method = self._build_title_method_instance()
            ratings = self._update_ratings(ratings, method.rate_sentences(document))
        if self._location_weight > 0.0:
            method = self._build_location_method_instance()
            ratings = self._update_ratings(ratings, method.rate_sentences(document))

        return self._get_best_sentences(document.sentences, sentences_count, ratings)
dataset/ETHPy150Open miso-belica/sumy/sumy/summarizers/edmundson.py/EdmundsonSummarizer.__call__/original