如何简化斯坦福法语词性标记返回的部分?将英语句子读入到NLTK中,找到每个单词的词性是相当容易的,然后使用map_tag()来简化标记集:
有人知道如何简化斯坦福词性标注器中法语模型使用的默认标签集吗?非常感谢其他人可以提供的任何见解。
#!/usr/bin/python
# -*- coding: utf-8 -*-
import os
from nltk.tag.stanford import POSTagger
from nltk.tokenize import word_tokenize
from nltk.tag import map_tag
#set java_home path from within script. Run os.getenv("JAVA_HOME") to test java_home
os.environ["JAVA_HOME"] = "C:\\Program Files\\Java\\jdk1.7.0_25\\bin"
english = u"the whole earth swarms with living beings, every plant, every grain and leaf, supports the life of thousands."
path_to_english_model = "C:\\Text\\Professional\\Digital Humanities\\Packages and Tools\\Stanford Packages\\stanford-postagger-full-2014-08-27\\stanford-postagger-full-2014-08-27\\models\\english-bidirectional-distsim.tagger"
path_to_jar = "C:\\Text\\Professional\\Digital Humanities\\Packages and Tools\\Stanford Packages\\stanford-postagger-full-2014-08-27\\stanford-postagger-full-2014-08-27\\stanford-postagger.jar"
#define english and french taggers
english_tagger = POSTagger(path_to_english_model, path_to_jar, encoding="utf-8")
#each tuple in list_of_english_pos_tuples = (word, pos)
list_of_english_pos_tuples = english_tagger.tag(word_tokenize(english))
simplified_pos_tags_english = [(word, map_tag('en-ptb', 'universal', tag)) for word, tag in list_of_english_pos_tuples]
print simplified_pos_tags_english
#output = [(u'the', u'DET'), (u'whole', u'ADJ'), (u'earth', u'NOUN'), (u'swarms', u'NOUN'), (u'with', u'ADP'), (u'living', u'NOUN'), (u'beings', u'NOUN'), (u',', u'.'), (u'every', u'DET'), (u'plant', u'NOUN'), (u',', u'.'), (u'every', u'DET'), (u'grain', u'NOUN'), (u'and', u'CONJ'), (u'leaf', u'NOUN'), (u',', u'.'), (u'supports', u'VERB'), (u'the', u'DET'), (u'life', u'NOUN'), (u'of', u'ADP'), (u'thousands', u'NOUN'), (u'.', u'.')]
但我不确定如何将以下代码返回的法语标签映射到通用标签集:
#!/usr/bin/python
# -*- coding: utf-8 -*-
import os
from nltk.tag.stanford import POSTagger
from nltk.tokenize import word_tokenize
from nltk.tag import map_tag
#set java_home path from within script. Run os.getenv("JAVA_HOME") to test java_home
os.environ["JAVA_HOME"] = "C:\\Program Files\\Java\\jdk1.7.0_25\\bin"
french = u"Chaque plante, chaque graine, chaque particule de matière organique contient des milliers d'atomes animés."
path_to_french_model = "C:\\Text\\Professional\\Digital Humanities\\Packages and Tools\\Stanford Packages\\stanford-postagger-full-2014-08-27\\stanford-postagger-full-2014-08-27\\models\\french.tagger"
path_to_jar = "C:\\Text\\Professional\\Digital Humanities\\Packages and Tools\\Stanford Packages\\stanford-postagger-full-2014-08-27\\stanford-postagger-full-2014-08-27\\stanford-postagger.jar"
french_tagger = POSTagger(path_to_french_model, path_to_jar, encoding="utf-8")
list_of_french_pos_tuples = french_tagger.tag(word_tokenize(french))
#up to this point all is well, but I'm not sure how to successfully create a simplified pos tagset with the French tuples
simplified_pos_tags_french = [(word, map_tag('SOME_ARGUMENT', 'universal', tag)) for word, tag in list_of_french_pos_tuples]
print simplified_pos_tags_french
有人知道如何简化斯坦福词性标注器中法语模型使用的默认标签集吗?非常感谢其他人可以提供的任何见解。