NLTK:从字符串中提取实体名称

Question

Python和NLTK noob在这里。跟什么混在一起。

我有一个字符串，其中包含pdf文档中的文本，我正在尝试使用nltk库提取实体名称

with open(filename, 'r') as f:
str_output = f.readlines()   
str_output = clean_str(str(str_output))
sentences = nltk.sent_tokenize(str_output)
tokenized_sentences = [nltk.word_tokenize(sentence) for sentence in sentences]
tagged_sentences = [nltk.pos_tag(sentence) for sentence in tokenized_sentences]
chunked_sentences = nltk.ne_chunk_sents(tagged_sentences, binary=True)

我完成了导入数据、清理字符串和预处理字符串的步骤。如何从字符串中获取不同的实体名称？

Answer 1

这应该有效：

import nltk
with open('sample.txt', 'r') as f:
sample = f.read()
sentences = nltk.sent_tokenize(sample)
tokenized_sentences = [nltk.word_tokenize(sentence) for sentence in sentences]
tagged_sentences = [nltk.pos_tag(sentence) for sentence in tokenized_sentences]
chunked_sentences = nltk.ne_chunk_sents(tagged_sentences, binary=True)
def extract_entity_names(t):
entity_names = []
if hasattr(t, 'node') and t.node:
if t.node == 'NE':
entity_names.append(' '.join([child[0] for child in t]))
else:
for child in t:
entity_names.extend(extract_entity_names(child))
return entity_names
entity_names = []
for tree in chunked_sentences:
# Print results per sentence
# print extract_entity_names(tree)
entity_names.extend(extract_entity_names(tree))
# Print all entity names
#print entity_names
# Print unique entity names
print set(entity_names)