从NLTK2.0.4到NLTK3.0的NLTK实体提取差异

Question

我遇到了一个问题，试图运行一个实体提取函数。我相信这是版本的不同。下面的工作示例在2.0.4中运行，但在3.0中不运行。我确实更改了一个函数调用: batch_ne_chunk到: nltk.ne_chunk_sents，以防止在3.0中抛出错误。

def package_get_entities(self,text):
    #text = text[0:300]
    entity_names = []
    chunked = self.get_chunked_sentences(text)
    for tree in chunked:
        entity_names.extend(self.extract_entity_names(tree))
    entity_names = list(set(entity_names))
    return entity_names

def get_chunked_sentences(self,text):
    sentences = nltk.sent_tokenize(text)
    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)
    return chunked_sentences

def extract_entity_names(self,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(self.extract_entity_names(child))
    return entity_names

运行功能：

str = 'this is some text about a man named Abraham Lincoln'
entArray = package_get_entities(str)

在2.0.4中，亚伯拉罕·林肯在3.0中产出[]

Answer 1

我不得不重写：

if hasattr(t, 'node') and t.node:

至：

if hasattr(t, 'label'):