o
    h                     @   s   d dl Z d dlZd dlZ	 dd ZdddZdddZdd	d
Zdd ZedkrLe 	 Z
e
jdeddd e
jddddd e
 Zeejejd dS dS )    Nc                 C   s0   | sdS | dkr
dS | dkrdS | dkrdS dS )	z
    Project the classes IJC used to 4 classes with more human-readable names

    The trained result is a pile, as I inadvertently taught my
    daughter to call horrible things, but leaving them with the
    original classes is also a pile
    ONEPPERNEOORGNELLOCMISC )tagr
   r
   `/var/www/html/env_mimamsha/lib/python3.10/site-packages/stanza/utils/datasets/ner/convert_ijc.pyconvert_tag   s   r   Tc                 C   s  g }d}t | (}g }d}d}d}d}	|D ]}
|d }|
 }
|
s$q|
ds.|
dr7|r6J d|  q|
drE|rDJ d|  q|
d	rT|rQ|| g }q|
d
krv|sbJ d| |f |	d }	|	dk rod}d}	n|	dkrud}q|
d}|d dkr|d dksJ d| |f d}q|d dkr|	d }	|	dkrt|dk rd}q|d d dkr|d d dksJ d| ||d f |d dd dd\}}|d d||f ksJ d| ||d f d}d}t|}q|r |r |r|r||d d| f q||d d| f d}q||d |f q||d df qW d   n	1 s5w   Y  |rCJ d|  |S )zC
    Reads an IJC NER file and returns a list of list of lines
    r   F   z<Storyz</Story>z%File %s had an unexpected <Story> tagz	<SentencezFile %s has a nested sentencez</Sentence>z))z?File %s closed a sentence when there was no open sentence at %d	0z((z*File %s has an unexpected first line at %dT   N   <>z.File %s has an unexpected tag format at %d: %s=z<%s=%s>zI-zB-r   zFile %s is unclosed!)openstrip
startswithappendsplitlenr   )
input_file
bio_format	sentenceslinenofincurrent_sentencein_nerin_sentenceprinted_firstnestinglinepiecesr   ner
   r
   r   read_single_file   s|   




6*Cr*   c                 C   s"   g }| D ]
}| t|| q|S )N)extendr*   )input_filesr   r   r   r
   r
   r   read_ijc_filesi   s   r-   c                 C   sf   t | |}t|d}|D ]}|D ]	}|d|  q|d qW d    d S 1 s,w   Y  d S )Nwz%s	%s

)r-   r   write)r,   csv_filer   r   foutsentencewordr
   r
   r   convert_ijco   s   
"r5   c                 C   sv   t d g }g }| D ]}t   dk r|| q|| qt|dks+t|dkr/tdt|| t|| dS )z
    Randomly splits the given list of input files into a train/dev with 85/15 split

    The original datasets only have train & test
    i  g333333?r   z*Not enough files to split into train & devN)randomseedr   r   RuntimeErrorr5   )r,   	train_csvdev_csvtrain_files	dev_filesfilenamer
   r
   r   convert_split_ijcw   s   

r>   __main__z--output_pathz*/home/john/stanza/data/ner/hi_ijc.test.csvzWhere to output the results)typedefaulthelpr,   N+zinput files to process)metavarnargsrB   F)T)argparser6   sysr   r*   r-   r5   r>   __name__ArgumentParserparseradd_argumentstr
parse_argsargsr,   output_pathr
   r
   r
   r   <module>   s     

L
