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python - 如何在 Google Colab 上运行 Stanford CoreNLP 进行词形还原？

问题描述

有一个类似的问题，但是从那时起 google colab 发生了很大变化，我想知道如何在 Google Colab 上使用 Stanford CoreNLP，特别是用于词形还原。

预期答案：

使用代码：

!pip install stanfordnlp
import stanfordnlp
stanfordnlp.download("es")
nlp = stanfordnlp.Pipeline(processors='tokenize,mwt,pos,lemma')
doc = nlp("Barack Obama was born in Hawaii.")
print(*[f'word: {word.text+" "}\tlemma: {word.lemma}' for sent in doc.sentences for word in sent.words], sep='\n')

%tb

------------
Loading: tokenize
With settings: 
{'model_path': '/root/stanfordnlp_resources/en_ewt_models/en_ewt_tokenizer.pt', 'lang': 'en', 'shorthand': 'en_ewt', 'mode': 'predict'}
Cannot load model from /root/stanfordnlp_resources/en_ewt_models/en_ewt_tokenizer.pt
An exception has occurred, use %tb to see the full traceback.

SystemExit: 1

/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py:2890: UserWarning: To exit: use 'exit', 'quit', or Ctrl-D.
  warn("To exit: use 'exit', 'quit', or Ctrl-D.", stacklevel=1)

任何改进问题的建议都将被考虑

标签： pythonstanford-nlpgoogle-colaboratory

解决方案

也许最好使用新的StanfordNLP而不是旧的CoreNLP。

!pip install stanfordnlp
import stanfordnlp
stanfordnlp.download("en")
nlp = stanfordnlp.Pipeline(processors='tokenize,mwt,pos,lemma')
doc = nlp("Barack Obama was born in Hawaii.")
print(*[f'word: {word.text+" "}\tlemma: {word.lemma}' for sent in doc.sentences for word in sent.words], sep='\n')

你会得到这个输出

word: Barack    lemma: Barack
word: Obama     lemma: Obama
word: was   lemma: be
word: born  lemma: bear
word: in    lemma: in
word: Hawaii    lemma: Hawaii
word: .     lemma: .

这是一个示例笔记本。

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