66b1607902649bd2639697b01b598bb7d796c443,soynlp/lemmatizer/_predicator.py,PredicatorExtractor,_predicator_lemma_candidates,#PredicatorExtractor#Any#Any#,350

Before Change

                lemmas[eojeol] = lemma_candidates

        if self.verbose:
            print("\r[Eomi Extractor] lemma candidates was done     ", flush=True)

        return lemmas

After Change

        for i_eojeol, eojeol in enumerate(eojeols):

            if self.verbose and i_eojeol % 1000 == 0:
                perc = "%.3f"% (100 * i_eojeol / n_eojeols)
                message = "lemma candidates ... {} %".format(perc)
                self._print(message, replace=True, newline=False)

            n = len(eojeol)
            lemma_candidates = set()

            for i in range(1, n+1):
                l, r = eojeol[:i], eojeol[i:]
                for stem, eomi in _lemma_candidate(l, r):
                    if (stem in self._stems) and (eomi, self._eomis):
                        lemma_candidates.add((stem, eomi, "Both"))
                    elif (stem in self._stems):
                        lemma_candidates.add((stem, eomi, "Only stem"))
                    elif (eomi in self._eomis):
                        lemma_candidates.add((stem, eomi, "Only eomi"))

            if lemma_candidates:
                lemmas[eojeol] = lemma_candidates

        if self.verbose:
            message = "lemma candidating was done     "
            self._print(message, replace=True, newline=True)

        return lemmas

Instances