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d„Zdd„Zddededefd„Zd	„ Zy)ÚWordNetLemmatizera»  
    WordNet Lemmatizer

    Provides 3 lemmatizer modes: _morphy(), morphy() and lemmatize().

    lemmatize() is a permissive wrapper around _morphy().
    It returns the shortest lemma found in WordNet,
    or the input string unchanged if nothing is found.

    >>> from nltk.stem import WordNetLemmatizer as wnl
    >>> print(wnl().lemmatize('us', 'n'))
    u

    >>> print(wnl().lemmatize('Anythinggoeszxcv'))
    Anythinggoeszxcv

    c                 ó4   — ddl m} |j                  |||«      S )zò
        _morphy() is WordNet's _morphy lemmatizer.
        It returns a list of all lemmas found in WordNet.

        >>> from nltk.stem import WordNetLemmatizer as wnl
        >>> print(wnl()._morphy('us', 'n'))
        ['us', 'u']
        é    ©Úwordnet)Únltk.corpusr   Ú_morphy©ÚselfÚformÚposÚcheck_exceptionsÚwns        úf/home/mcse/projects/srt_converter/srt-converter-venv/lib/python3.12/site-packages/nltk/stem/wordnet.pyr	   zWordNetLemmatizer._morphy   s   € õ 	.à�z‰z˜$ Ð%5Ó6Ð6ó    Nc                 ó4   — ddl m} |j                  |||«      S )aI  
        morphy() is a restrictive wrapper around _morphy().
        It returns the first lemma found in WordNet,
        or None if no lemma is found.

        >>> from nltk.stem import WordNetLemmatizer as wnl
        >>> print(wnl().morphy('us', 'n'))
        us

        >>> print(wnl().morphy('catss'))
        None
        r   r   )r   r   Úmorphyr
   s        r   r   zWordNetLemmatizer.morphy+   s   € õ 	.à�y‰y˜˜sÐ$4Ó5Ð5r   Úwordr   Úreturnc                 óP   — | j                  ||«      }|rt        |t        ¬«      S |S )a±  Lemmatize `word` by picking the shortest of the possible lemmas,
        using the wordnet corpus reader's built-in _morphy function.
        Returns the input word unchanged if it cannot be found in WordNet.

        >>> from nltk.stem import WordNetLemmatizer as wnl
        >>> 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

        :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.
        :type pos: str
        :return: The shortest lemma of `word`, for the given `pos`.
        )Úkey)r	   ÚminÚlen)r   r   r   Úlemmass       r   Ú	lemmatizezWordNetLemmatizer.lemmatize<   s(   € ð2 —‘˜d CÓ(ˆÙ'-Œs�6œsÔ#Ð7°4Ð7r   c                  ó   — y)Nz<WordNetLemmatizer>© )r   s    r   Ú__repr__zWordNetLemmatizer.__repr__X   s   € Ø$r   )T)NT)Ún)	Ú__name__Ú
__module__Ú__qualname__Ú__doc__r	   r   Ústrr   r   r   r   r   r   r      s0   „ ñó$7ó6ñ"8˜cð 8¨ð 8°có 8ó8%r   r   N)r   r   r   r   ú<module>r%      s   ð÷N%ò N%r   