# Natural Language Toolkit: WordNet stemmer interface
#
# Copyright (C) 2001-2023 NLTK Project
# Author: Steven Bird <stevenbird1@gmail.com>
#         Edward Loper <edloper@gmail.com>
# URL: <https://www.nltk.org/>
# For license information, see LICENSE.TXT

from nltk.corpus import wordnet as wn


class WordNetLemmatizer:
    """
    WordNet Lemmatizer

    Lemmatize using WordNet's built-in morphy function.
    Returns the input word unchanged if it cannot be found in WordNet.

        >>> from nltk.stem import WordNetLemmatizer
        >>> wnl = WordNetLemmatizer()
        >>> print(wnl.lemmatize('dogs'))
        dog
        >>> print(wnl.lemmatize('churches'))
        church
        >>> print(wnl.lemmatize('aardwolves'))
        aardwolf
        >>> print(wnl.lemmatize('abaci'))
        abacus
        >>> print(wnl.lemmatize('hardrock'))
        hardrock
    """

    def lemmatize(self, word: str, pos: str = "n") -> str:
        """Lemmatize `word` using WordNet's built-in morphy function.
        Returns the input word unchanged if it cannot be found in WordNet.

        :param word: The input word to lemmatize.
        :type word: str
        :param pos: The Part Of Speech tag. Valid options are `"n"` for nouns,
            `"v"` for verbs, `"a"` for adjectives, `"r"` for adverbs and `"s"`
            for satellite adjectives.
        :param pos: str
        :return: The lemma of `word`, for the given `pos`.
        """
        lemmas = wn._morphy(word, pos)
        return min(lemmas, key=len) if lemmas else word

    def __repr__(self):
        return "<WordNetLemmatizer>"