从文件路径中提取人名

Question

我正试图从文件路径中提取所有人名。我的方法是将文件路径拆分为单个单词，然后应用NTLK的词性标记来识别专有名词，然后使用ne_chunk函数来识别人员

import nltk
import re


def extract_entities(y):
    #make an empty list to receive results of operation
    AggPeople = []
    #split the filepath by backslashes
    for y in y.split("\\"):
        #separate the product above into words, then attach nltk tags (ie. NNP), then attach more specific ntlk tags (ie. Person)
        for chunk in nltk.ne_chunk(nltk.pos_tag(re.findall(r"[\w]+", y))) :
            #filter out everything but the person labels
            if hasattr(chunk, 'label') and chunk.label() == "PERSON":
                #bring the results of the above into a list
                AggPeople.append(' '.join(c[0] for c in chunk.leaves()).capitalize())
                #filter out words you don't want
                AggPeople = [x for x in AggPeople if (x not in ['Schedules','Old'])]
    #get rid of duplicate words with 'set'
    return set(AggPeople)

text = "O:\Country\Province\District\city\Cricket, Jimmy (Y1617F)\Old Schedules\Cricket, Jimmy (78655) Golick doo wop 7 Sept 2016.xlsx"

print(extract_entities(text))

问题是结果是“Jimmy y1617f”，我希望它是“Jimmy”

我认为nltk.ne_chunk是以一种在处理文本时有意义的方式对单词进行分组，而不是在处理文件路径时。为了解决这个问题，我尝试定义我自己的nltk.ne_chunk等价物，如下所示：

import nltk
import re
from nltk import RegexpParser
def extract_entities(y):
    AggPeople = []
    patterns= r"<NP:{<NNP>+}"
    chunker = RegexpParser(patterns)
    print(chunker)
    for y in y.split("\\"):
        for chunk in chunker(nltk.pos_tag(re.findall(r"[\w]+", y))) :
            if hasattr(chunk, 'label') and chunk.label() == "PERSON":
                AggPeople.append(' '.join(c[0] for c in chunk.leaves()).capitalize())
                AggPeople = [x for x in AggPeople if (x not in ['Schedules','Old'])]
    return set(AggPeople)

收到错误代码：

'RegexpParser' object is not callable

完全回溯：

chunk.RegexpParser with 1 stages:
RegexpChunkParser with 1 rules:
       <ChunkRule: '<NNP>'>
Traceback (most recent call last):

  File "<ipython-input-282-cb323eff63b4>", line 1, in <module>
    runfile('C:/Users//.spyder-py3/ExtractingNames.py', wdir='C:/Users//.spyder-py3')

  File "C:\spydercustomize.py", line 827, in runfile
    execfile(filename, namespace)

  File "C:\spydercustomize.py", line 110, in execfile
    exec(compile(f.read(), filename, 'exec'), namespace)

  File "C:/Users//.spyder-py3/ExtractingNames.py", line 32, in <module>
    print(extract_entities(text))

  File "C:/Users//.spyder-py3/ExtractingNames.py", line 23, in extract_entities
    for chunk in chunker(nltk.pos_tag(re.findall(r"[\w]+", y))) :

TypeError: 'RegexpParser' object is not callable

Answer 1

#looks for two proper nouns side-by-side
patterns= r"P:{<NNP>{2}}"
chunker = nltk.RegexpParser(patterns)    

def extract_entities(y):
    AggPeople = []
    for y in y.split("\\"):
        #excludes words with digits and schedules
        for chunk in chunker.parse(nltk.pos_tag(re.findall(r"\b(?!Schedules|Old)[^\d\W]+\b", y))) :
            if hasattr(chunk, 'label') and chunk.label() == "P" :
                AggPeople.append(' '.join(c[0] for c in chunk.leaves()).capitalize())
    return set(AggPeople)

text = "O:\Country\Province\District\city\Cricket, Jimmy (Y1617F)\Old Schedules\Cricket, Jimmy (78655) Golick doo wop 7 Sept 2016.xlsx"

print(extract_entities(text))

• 如果将chunker放在循环之外，可以使代码运行得更快（否则，它会随着循环的每次迭代而重新生成）
• 如果您正在查找人名，并且通常有两个人名（第一个和最后一个），则可以在模式中使用{2}符号指定两个NNP
• 您可以使用负前瞻排除正则表达式中的某些单词，并使用^\d排除其中包含数字的单词