这是我的问题的后续行动.我正在使用nltk解析人员,组织及其关系.通过这个例子,我能够创建大量的人员和组织; 但是,我在nltk.sem.extract_rel命令中收到错误:
AttributeError: 'Tree' object has no attribute 'text'
这是完整的代码:
import nltk
import re
#billgatesbio from http://www.reuters.com/finance/stocks/officerProfile?symbol=MSFT.O&officerId=28066
with open('billgatesbio.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.batch_ne_chunk(tagged_sentences)
# tried plain ne_chunk instead of batch_ne_chunk as given in the book
#chunked_sentences = [nltk.ne_chunk(sentence) for sentence in tagged_sentences]
# pattern to find <person> served as <title> in <org> …