August 2022
Intermediate to advanced
441 pages
11h 26m
Chinese
Content preview from Python文本分析
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372
｜
第
12
章
12.5.5
命名规范化
尽管我们的命名消解统一了文章内公司的指称，但这个公司名在各个文章之间仍
然不统一。在某一篇文章中叫做“
Hughes Tool Co
”，而其他文章中则叫“
Hughes
Tool
”。实体链接器可以将不同的实体指称链接到唯一的规范表示，但是由于没有
实体链接器，因此我们将使用（已消解的）命名实体作为唯一的识别符。由于在共
指消解的环节，消解后的名称总是第一次出现的名称，而且通常都是文章中最完整
的指代，因此出错的可能性不会太大。
此外，我们还需要删除公司名称中的后缀“
Co.
”或“
Inc.
”。下列函数使用了一个
正则表达式来处理这个操作：
def strip_legal_suffix(text):
return re.sub(r'(\s+and)?(\s+|\b(Co|Corp|Inc|Plc|Ltd)\b\.?)*$', '', text)
print(strip_legal_suffix('Hughes Tool Co'))
输出结果：
Hughes Tool
流水线的最后一个函数
norm_names
，针对存储在
ref_n
属性的每个已消解共指的组
织名，应用最后的规范化。注意，在这种方式下，“
Hughes
”（
PERSON
）与“
Hughes
”
（
ORG
）仍然是不同的实体。
def norm_names(doc):
for t in doc:
if t._.ref_n != '' and t._.ref_t in ['ORG']:
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.