# 分词 tokens = nltk.word_tokenize(sentence) # 词性标注 pos_tags = nltk.pos_tag(tokens) # 打印结果 print(pos_tags) 输出结果如下: 代码语言:txt 复制 [('I', 'PRP'), ('love', 'VBP'), ('using', 'VBG'), ('NLTK', 'NNP'), ('for', 'IN'), ('natural', 'JJ'), ('...
我们将它们从每个句子的标签列表转换为一维 tensor(total\_num\_tags),即 batch input 中的标签总数。 这样我们可以将批处理后的 gold label 直接传递给损失函数。 Padding the data 由于句子的长度可以变化,我们的输入数据是不同大小的 tensor 列表。 因此,为了通过 LSTM forward 它们,我们需要 pad 它们。 在之...
pos_tags将返回一个包含词语及其对应词性标签的列表。每个元素是一个元组,包含词语和其对应的词性标签。例如,对于上述示例句子,pos_tags的结果可能如下所示: 代码语言:python 代码运行次数:0 复制Cloud Studio 代码运行 [('This', 'DT'), ('is', 'VBZ'), ('a', 'DT'), ('sample', 'JJ'), ('sente...
from spacy.lang.zh import Chinese nlp = Chinese() doc = nlp(u"蘋果公司正考量用一億元買下英國的新創公司") doc.ents # returns (), i.e. empty tuple for word in doc: print(word.text, word.pos_) ''' returns 蘋果 公司 正 考量 用 一 億元 買 下 英國 的 新創 公司 ''' I am ne...
The group of labels/tags used to tag the words is known as tagset. Pos tagging helps in information retrieval, question answering, word sense disambiguation, etc. Example- I will book a flight to India. I am reading a book. In both sentences, the word "book" is used. But, in the fi...
The stochastic methods are uni-gram, bi-gram, tri-gram, unigram+bigram, unigram+bigram+trigram, Hidden Markov Model (HMM), Conditional Random Forest (CRF), Trigrams 'n' Tags (TnT) whereas the transformation methods are Brill with the combination of previously mentioned stochastic techniques. A ...
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tags=nlp.pos_tag(text) print(tags) 运行以上代码,输出结果与NLTK中的pos函数类似。 3. Jieba中的pos函数 Jieba是Python中常用的中文分词工具,也提供了词性标注的功能。使用Jieba中的pos函数可以对中文文本进行词性标注。 以下是在Jieba中使用pos函数的示例代码: importjieba.possegaspseg # 使用pos函数进行词性标注...
52 self.tag_vocab.update(tags) ~/opt/miniconda3/envs/nlp/lib/python3.8/site-packages/hanlp/transform/tsv.py in file_to_inputs(self, filepath, gold) 68 def file_to_inputs(self, filepath: str, gold=True): 69 assert gold, ‘TsvTaggingFormat does not support reading non-gold files’...
And thepos_tagfunction thinks is a normal sentence hence giving the tags: >>>sent3 ='skydiving skydiving skydiving'.split()>>>pos_tag(sent3) [('skydiving','VBG'), ('skydiving','NN'), ('skydiving','VBG')] In which case the first is a verb, the second word a noun a...