c2ba425358ed9d57139bba87b7716c544b85cc71,soynlp/pos/_news_pos.py,NewsPOSExtractor,_word_match_postprocessing,#NewsPOSExtractor#,112

Before Change

        if self._verbose:
            print("\r[POS Extractor] postprocessing was done 100.00 %    ")
            print("[POS Extractor] //// statistics ////")
            templates = "[POS Extractor] {} ({:.3f} %): {}"
            print(templates.format(len(nouns_), as_percent(nouns_), "Noun + [Josa/Predicator]"))
            print(templates.format(len(confused_nouns), as_percent(confused_nouns), "Confused nouns"))
            print(templates.format(len(adjectives_), as_percent(adjectives_), "[Noun] + Adjective"))
            print(templates.format(len(verbs_), as_percent(verbs_), "[Noun] + Verb"))
            print(templates.format(len(not_covered), as_percent(not_covered), "not covered"))

        return nouns_, confused_nouns, adjectives_, verbs_, not_covered

After Change

        if self._verbose:
            print("\r[POS Extractor] postprocessing was done 100.00 %    ")
            print("\n[POS Extractor] //// statistics ////")
            statistics = [
                (len(nouns_), as_percent(nouns_), "Noun + [Josa/Predicator]"),
                (len(confused_nouns), as_percent(confused_nouns), "Confused nouns"),
                (len(adjectives_), as_percent(adjectives_), "[Noun] + Adjective"),
                (len(verbs_), as_percent(verbs_), "[Noun] + Verb"),
                (len(not_covered), as_percent(not_covered), "not covered")
            ]
            for stats in statistics:
                print("[POS Extractor] {} ({:.3f} %): {}".format(*stats))

        return nouns_, confused_nouns, adjectives_, verbs_, not_covered

    def _word_match(self, word, references):
        if word in references:

Instances