如何在 Google Colab 上運行斯坦福 CoreNLP 進行詞形還原？

Question

有一個類似的問題，但是從那時起 google colab 發生了很大變化，我想知道如何在 Google Colab 上使用斯坦福 CoreNLP，專門用於詞形還原。

預期答案：

• 導入模塊
• 使用示例代碼進行詞形還原

使用代碼：

!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)

將考慮任何改進問題的建議

Answer 1

也許最好使用新的StanfordNLP而不是舊的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')

你會得到這個輸出

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: .

這是一個示例筆記本。