python - 如何提取标记标签中的文本？

Question

我有以下文档，我想提取所有类别标志。
输入 : 应该是一个具有非结构化文本的变量，名为 doc .

doc = "Like APC , <category="Modifier">APC2</category> regulates the formation of active betacatenin-Tcf 
       complexes , as demonstrated using transient transcriptional activation assays in APC - / - 
       <category="Modifier">colon carcinoma</category> cells. Human APC2 maps to chromosome 19p13 . 3 . 
       APC and APC2 may therefore have comparable functions in development 
       and <category="SpecificDisease">cancer</category>"

输出 : 应该如下:

{
'Modifier': ['APC2', 'colon carcinoma'],
'SpecificDisease': ['cancer']
}

这应该是自动化的，以便能够提取语料库中的所有类别标签。

我尝试了以下代码:

soup = BeautifulSoup(doc)
contents = soup.find_all('category')

但不知道如何提取每个标志。

Answer 1

BeautifulSoup 无法解析这种类型的文档。但作为“解决方法”，您可以使用 re模块，例如:

import re

doc = """Like APC , <category="Modifier">APC2</category> regulates the formation of active betacatenin-Tcf 
       complexes , as demonstrated using transient transcriptional activation assays in APC - / - 
       <category="Modifier">colon carcinoma</category> cells. Human APC2 maps to chromosome 19p13 . 3 . 
       APC and APC2 may therefore have comparable functions in development 
       and <category="SpecificDisease">cancer</category>"""

out = {}
for c, t in re.findall(r'<category="(.*?)">(.*?)</category>', doc):
    out.setdefault(c, []).append(t)

print(out)

打印:

{'Modifier': ['APC2', 'colon carcinoma'], 'SpecificDisease': ['cancer']}