<s> """<STR_LIT>""" <EOL> import nltk <EOL> from quepy . tagger import Word <EOL> from quepy . encodingpolicy import assert_valid_encoding <EOL> _penn_to_morphy_tag = { } <EOL> def penn_to_morphy_tag ( tag ) : <EOL> assert_valid_encoding ( tag ) <EOL> for penn , morphy in _penn_to_morphy_tag . iteritems ( ) : <EOL> if tag . startswith ( penn ) : <EOL> return morphy <EOL> return None <EOL> def run_nltktagger ( string , nltk_data_path = None ) : <EOL> """<STR_LIT>""" <EOL> assert_valid_encoding ( string ) <EOL> global _penn_to_morphy_tag <EOL> if nltk_data_path : <EOL> nltk . data . path = nltk_data_path <EOL> from nltk . corpus import wordnet <EOL> if not _penn_to_morphy_tag : <EOL> _penn_to_morphy_tag = { <EOL> u'<STR_LIT>' : wordnet . NOUN , <EOL> u'<STR_LIT>' : wordnet . ADJ , <EOL> u'<STR_LIT>' : wordnet . VERB , <EOL> u'<STR_LIT>' : wordnet . ADV , <EOL> } <EOL> tokens = nltk . wordpunct_tokenize ( string ) <EOL> tags = nltk . pos_tag ( tokens ) <EOL> words = [ ] <EOL> for token , pos in tags : <EOL> word = Word ( token ) <EOL> word . pos = pos . split ( "<STR_LIT:|>" ) [ <NUM_LIT:0> ] . decode ( "<STR_LIT:ascii>" ) <EOL> mtag = penn_to_morphy_tag ( word . pos ) <EOL> lemma = wordnet . morphy ( word . token , pos = mtag ) <EOL> if isinstance ( lemma , str ) : <EOL> lemma = lemma . decode ( "<STR_LIT:ascii>" ) <EOL> word . lemma = lemma <EOL> if word . lemma is None : <EOL> word . lemma = word . token . lower ( ) <EOL> words . append ( word ) <EOL> return words </s>
