Spacy 自定义分词器使用 Infix 正则表达式仅包含连字符词作为分词

Spacy custom tokenizer to include only hyphen words as tokens using Infix regex

我想包括带连字符的单词,例如:long-term、self-esteem、 等作为 Spacy 中的单个标记。在查看 Whosebug 上的一些类似帖子后,Github, its documentation and elsewhere,我还编写了一个自定义分词器,如下所示:

import re
from spacy.tokenizer import Tokenizer

prefix_re = re.compile(r'''^[\[\("']''')
suffix_re = re.compile(r'''[\]\)"']$''')
infix_re = re.compile(r'''[.\,\?\:\;\...\‘\’\`\“\”\"\'~]''')

def custom_tokenizer(nlp):
    return Tokenizer(nlp.vocab, prefix_search=prefix_re.search,
                                suffix_search=suffix_re.search,
                                infix_finditer=infix_re.finditer,
                                token_match=None)

nlp = spacy.load('en_core_web_lg')
nlp.tokenizer = custom_tokenizer(nlp)

doc = nlp(u'Note: Since the fourteenth century the practice of “medicine” has become a profession; and more importantly, it\'s a male-dominated profession.')
[token.text for token in doc]

所以对于这句话: '注:自十四世纪以来,“医学”实践已成为一种职业;更重要的是,它\'s a male-dominated profession.'

现在,合并自定义 Spacy Tokenizer 后的标记为:

'Note', ':', 'Since', 'the', 'fourteenth', 'century', 'the', 'practice' , 'of', '“药”, '', 'has', ';', 'become', 'a' , 'profession', ',', 'and', 'more', 'importantly', ',', "it's", 'a', '男性主导', 'profession', '.'

早些时候,此更改之前的令牌是:

'Note', ':', 'Since', 'the', 'fourteenth', 'century', 'the', 'practice' , 'of', '', '医药', '', 'has', 'become', 'a', 'profession', ';', 'and', 'more', 'importantly', ',', ' ', "", 'a', '', '-', '支配', 'profession', '.'

而且,预期的标记应该是:

'Note', ':', 'Since', 'the', 'fourteenth', 'century', 'the', 'practice' , 'of', '', '医药', '', 'has', 'become', 'a', 'profession', ';', 'and', 'more', 'importantly', ',', ' it', "'s", 'a', '男性主导', 'profession', '.'

总结: 可以看出...

使用默认的 prefix_re 和 suffix_re 给出了预期的输出:

import re
import spacy
from spacy.tokenizer import Tokenizer
from spacy.util import compile_prefix_regex, compile_infix_regex, compile_suffix_regex

def custom_tokenizer(nlp):
    infix_re = re.compile(r'''[.\,\?\:\;\...\‘\’\`\“\”\"\'~]''')
    prefix_re = compile_prefix_regex(nlp.Defaults.prefixes)
    suffix_re = compile_suffix_regex(nlp.Defaults.suffixes)

    return Tokenizer(nlp.vocab, prefix_search=prefix_re.search,
                                suffix_search=suffix_re.search,
                                infix_finditer=infix_re.finditer,
                                token_match=None)

nlp = spacy.load('en')
nlp.tokenizer = custom_tokenizer(nlp)

doc = nlp(u'Note: Since the fourteenth century the practice of “medicine” has become a profession; and more importantly, it\'s a male-dominated profession.')
[token.text for token in doc]

['Note', ':', 'Since', 'the', 'fourteenth', 'century', 'the', 'practice', 'of', '“', 'medicine', '”', 'has', 'become', 'a', 'profession', ';', 'and', 'more', 'importantly', ',', 'it', "'s", 'a', 'male-dominated', 'profession' , '.']

如果你想深入了解为什么你的正则表达式不像 SpaCy 那样工作,这里有相关源代码的链接:

此处定义的前缀和后缀:

https://github.com/explosion/spaCy/blob/master/spacy/lang/punctuation.py

参考此处定义的字符(例如引号、连字符等):

https://github.com/explosion/spaCy/blob/master/spacy/lang/char_classes.py

以及用于编译它们的函数(例如,compile_prefix_regex):

https://github.com/explosion/spaCy/blob/master/spacy/util.py