Ë
    çÍ:j   ã                   óf   — d dl Z d dlZd dlZd dlZd dlZd dlmZ d dlmZ d dl	m
Z
  G d„ de
«      Zy)é    N)ÚZipFilePathPointer)Úfind_dir)Ú
TokenizerIc                   óR   — e Zd ZdZd
d„Zd„ Zdd„Zd„ Zed„ «       Z	ed„ «       Z
d„ Zy	)ÚReppTokenizeraé  
    A class for word tokenization using the REPP parser described in
    Rebecca Dridan and Stephan Oepen (2012) Tokenization: Returning to a
    Long Solved Problem - A Survey, Contrastive  Experiment, Recommendations,
    and Toolkit. In ACL. http://anthology.aclweb.org/P/P12/P12-2.pdf#page=406

    >>> sents = ['Tokenization is widely regarded as a solved problem due to the high accuracy that rulebased tokenizers achieve.' ,
    ... 'But rule-based tokenizers are hard to maintain and their rules language specific.' ,
    ... 'We evaluated our method on three languages and obtained error rates of 0.27% (English), 0.35% (Dutch) and 0.76% (Italian) for our best models.'
    ... ]
    >>> tokenizer = ReppTokenizer('/home/alvas/repp/') # doctest: +SKIP
    >>> for sent in sents:                             # doctest: +SKIP
    ...     tokenizer.tokenize(sent)                   # doctest: +SKIP
    ...
    (u'Tokenization', u'is', u'widely', u'regarded', u'as', u'a', u'solved', u'problem', u'due', u'to', u'the', u'high', u'accuracy', u'that', u'rulebased', u'tokenizers', u'achieve', u'.')
    (u'But', u'rule-based', u'tokenizers', u'are', u'hard', u'to', u'maintain', u'and', u'their', u'rules', u'language', u'specific', u'.')
    (u'We', u'evaluated', u'our', u'method', u'on', u'three', u'languages', u'and', u'obtained', u'error', u'rates', u'of', u'0.27', u'%', u'(', u'English', u')', u',', u'0.35', u'%', u'(', u'Dutch', u')', u'and', u'0.76', u'%', u'(', u'Italian', u')', u'for', u'our', u'best', u'models', u'.')

    >>> for sent in tokenizer.tokenize_sents(sents): # doctest: +SKIP
    ...     print(sent)                              # doctest: +SKIP
    ...
    (u'Tokenization', u'is', u'widely', u'regarded', u'as', u'a', u'solved', u'problem', u'due', u'to', u'the', u'high', u'accuracy', u'that', u'rulebased', u'tokenizers', u'achieve', u'.')
    (u'But', u'rule-based', u'tokenizers', u'are', u'hard', u'to', u'maintain', u'and', u'their', u'rules', u'language', u'specific', u'.')
    (u'We', u'evaluated', u'our', u'method', u'on', u'three', u'languages', u'and', u'obtained', u'error', u'rates', u'of', u'0.27', u'%', u'(', u'English', u')', u',', u'0.35', u'%', u'(', u'Dutch', u')', u'and', u'0.76', u'%', u'(', u'Italian', u')', u'for', u'our', u'best', u'models', u'.')
    >>> for sent in tokenizer.tokenize_sents(sents, keep_token_positions=True): # doctest: +SKIP
    ...     print(sent)                                                         # doctest: +SKIP
    ...
    [(u'Tokenization', 0, 12), (u'is', 13, 15), (u'widely', 16, 22), (u'regarded', 23, 31), (u'as', 32, 34), (u'a', 35, 36), (u'solved', 37, 43), (u'problem', 44, 51), (u'due', 52, 55), (u'to', 56, 58), (u'the', 59, 62), (u'high', 63, 67), (u'accuracy', 68, 76), (u'that', 77, 81), (u'rulebased', 82, 91), (u'tokenizers', 92, 102), (u'achieve', 103, 110), (u'.', 110, 111)]
    [(u'But', 0, 3), (u'rule-based', 4, 14), (u'tokenizers', 15, 25), (u'are', 26, 29), (u'hard', 30, 34), (u'to', 35, 37), (u'maintain', 38, 46), (u'and', 47, 50), (u'their', 51, 56), (u'rules', 57, 62), (u'language', 63, 71), (u'specific', 72, 80), (u'.', 80, 81)]
    [(u'We', 0, 2), (u'evaluated', 3, 12), (u'our', 13, 16), (u'method', 17, 23), (u'on', 24, 26), (u'three', 27, 32), (u'languages', 33, 42), (u'and', 43, 46), (u'obtained', 47, 55), (u'error', 56, 61), (u'rates', 62, 67), (u'of', 68, 70), (u'0.27', 71, 75), (u'%', 75, 76), (u'(', 77, 78), (u'English', 78, 85), (u')', 85, 86), (u',', 86, 87), (u'0.35', 88, 92), (u'%', 92, 93), (u'(', 94, 95), (u'Dutch', 95, 100), (u')', 100, 101), (u'and', 102, 105), (u'0.76', 106, 110), (u'%', 110, 111), (u'(', 112, 113), (u'Italian', 113, 120), (u')', 120, 121), (u'for', 122, 125), (u'our', 126, 129), (u'best', 130, 134), (u'models', 135, 141), (u'.', 141, 142)]
    c                 óp   — | j                  |«      | _        t        j                  «       | _        || _        y )N)Úfind_repptokenizerÚrepp_dirÚtempfileÚ
gettempdirÚworking_dirÚencoding)Úselfr
   r   s      úg/home/mcse/projects/srt_converter/srt-converter-venv/lib/python3.12/site-packages/nltk/tokenize/repp.pyÚ__init__zReppTokenizer.__init__6   s,   € Ø×/Ñ/°Ó9ˆŒä#×.Ñ.Ó0ˆÔà ˆ�ó    c                 ó8   — t        | j                  |g«      «      S )zÈ
        Use Repp to tokenize a single sentence.

        :param sentence: A single sentence string.
        :type sentence: str
        :return: A tuple of tokens.
        :rtype: tuple(str)
        )ÚnextÚtokenize_sents)r   Úsentences     r   ÚtokenizezReppTokenizer.tokenize=   s   € ô �D×'Ñ'¨¨
Ó3Ó4Ð4r   c              #   óÜ  K  — t        j                  d| j                  dd¬«      5 }|D ]  }|j                  t	        |«      dz   «       Œ! |j                  «        | j                  |j                  «      }| j                  |«      j                  | j                  «      j                  «       }| j                  |«      D ]  }|st        |Ž \  }}}	|–— Œ 	 ddd«       y# 1 sw Y   yxY w­w)zà
        Tokenize multiple sentences using Repp.

        :param sentences: A list of sentence strings.
        :type sentences: list(str)
        :return: A list of tuples of tokens
        :rtype: iter(tuple(str))
        zrepp_input.ÚwF)ÚprefixÚdirÚmodeÚdeleteú
N)r   ÚNamedTemporaryFiler   ÚwriteÚstrÚcloseÚgenerate_repp_commandÚnameÚ_executeÚdecoder   ÚstripÚparse_repp_outputsÚzip)
r   Ú	sentencesÚkeep_token_positionsÚ
input_fileÚsentÚcmdÚrepp_outputÚtokenized_sentÚstartsÚendss
             r   r   zReppTokenizer.tokenize_sentsH   sÜ   è ø€ ô ×(Ñ(Ø  d×&6Ñ&6¸SÈô
ð 	%àà!ò 3�Ø× Ñ ¤ T£¨TÑ!1Õ2ð3à×ÑÔà×,Ñ,¨Z¯_©_Ó=ˆCàŸ-™-¨Ó,×3Ñ3°D·M±MÓB×HÑHÓJˆKØ"&×"9Ñ"9¸+Ó"Fò %�Ù+ä36¸Ð3GÑ0�N F¨DØ$Ó$ñ	%÷	%÷ 	%ñ 	%üs   ‚$C,¦B0C Ã	C,Ã C)Ã%C,c                 óh   — | j                   dz   g}|d| j                   dz   gz  }|ddgz  }||gz  }|S )z«
        This module generates the REPP command to be used at the terminal.

        :param inputfilename: path to the input file
        :type inputfilename: str
        ú	/src/reppz-cú/erg/repp.setz--formatÚtriple)r
   )r   Úinputfilenamer.   s      r   r#   z#ReppTokenizer.generate_repp_commandb   sM   € ð �}‰}˜{Ñ*Ð+ˆØ��d—m‘m oÑ5Ð6Ñ6ˆØ�
˜HÐ%Ñ%ˆØ�ˆÑˆØˆ
r   c                 ó”   — t        j                  | t         j                  t         j                  ¬«      }|j                  «       \  }}|S )N)ÚstdoutÚstderr)Ú
subprocessÚPopenÚPIPEÚcommunicate)r.   Úpr9   r:   s       r   r%   zReppTokenizer._executeo   s2   € ä×Ñ˜S¬¯©ÄÇÁÔQˆØŸ™›‰ˆ�Øˆr   c              #   ó0  K  — t        j                  dt         j                  «      }| j                  d«      D ]S  }|j	                  |«      D ���cg c]  \  }}}|t        |«      t        |«      f‘Œ }}}}t        d„ |D «       «      }|–— ŒU yc c}}}w ­w)aZ  
        This module parses the tri-tuple format that REPP outputs using the
        "--format triple" option and returns an generator with tuple of string
        tokens.

        :param repp_output:
        :type repp_output: type
        :return: an iterable of the tokenized sentences as tuples of strings
        :rtype: iter(tuple)
        z^\((\d+), (\d+), (.+)\)$z

c              3   ó&   K  — | ]	  }|d    –— Œ y­w)é   N© )Ú.0Úts     r   ú	<genexpr>z3ReppTokenizer.parse_repp_outputs.<locals>.<genexpr>‡   s   è ø€ Ò= 1˜!˜A�$Ñ=ùs   ‚N)ÚreÚcompileÚ	MULTILINEÚsplitÚfindallÚintÚtuple)r/   Ú
line_regexÚsectionÚstartÚendÚtokenÚwords_with_positionsÚwordss           r   r(   z ReppTokenizer.parse_repp_outputsu   sš   è ø€ ô —Z‘ZÐ ;¼R¿\¹\ÓJˆ
Ø"×(Ñ(¨Ó0ò 	'ˆGð *4×);Ñ);¸GÓ)D÷$ð $á%�E˜3 ð œ˜E›
¤C¨£HÒ-ð$Ð ò $ô Ñ=Ð(<Ô=Ó=ˆEØ&Ó&ñ	'ùô$ùs   ‚ABÁ"B
Á2$Bc                 óô   — t         j                  j                  |«      r|}nt        |d¬«      }t         j                  j                  |dz   «      sJ ‚t         j                  j                  |dz   «      sJ ‚|S )zX
        A module to find REPP tokenizer binary and its *repp.set* config file.
        )ÚREPP_TOKENIZER)Úenv_varsr4   r5   )ÚosÚpathÚexistsr   )r   Úrepp_dirnameÚ	_repp_dirs      r   r	   z ReppTokenizer.find_repptokenizerŠ   sb   € ô �7‰7�>‰>˜,Ô'Ø$‰Iä  Ð8KÔLˆIä�w‰w�~‰~˜i¨+Ñ5Ô6Ð6Ð6Ü�w‰w�~‰~˜i¨/Ñ9Ô:Ð:Ð:ØÐr   N)Úutf8)F)Ú__name__Ú
__module__Ú__qualname__Ú__doc__r   r   r   r#   Ústaticmethodr%   r(   r	   rC   r   r   r   r      sI   „ ñó@!ò	5ó%ò4ð ñó ðð
 ñ'ó ð'ó(r   r   )rX   rG   r;   Úsysr   Ú	nltk.datar   Únltk.internalsr   Únltk.tokenize.apir   r   rC   r   r   ú<module>rg      s-   ðó 
Û 	Û Û 
Û å (Ý #Ý (ô@�Jõ @r   