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linguisticsweb:tutorials:linguistics_tutorials:automaticannotation:stanford_ner_tagger_python [2019/05/16 10:34]
sabinebartsch
linguisticsweb:tutorials:linguistics_tutorials:automaticannotation:stanford_ner_tagger_python [2019/05/16 10:34] (current)
sabinebartsch
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 This small example illustrates how the [[https://​nlp.stanford.edu/​software/​CRF-NER.shtml|Stanford Named Entity Recognizer (NER)]] can be driven from Python 3: This small example illustrates how the [[https://​nlp.stanford.edu/​software/​CRF-NER.shtml|Stanford Named Entity Recognizer (NER)]] can be driven from Python 3:
  
-<code python>+<sxh python>
 # Stanford NER 3.9.2 stand-alone version # Stanford NER 3.9.2 stand-alone version
 # classifier: english.muc.7class.distsim.crf.ser.gz # classifier: english.muc.7class.distsim.crf.ser.gz
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     print(x + "​_"​ + y)     print(x + "​_"​ + y)
  
-</code>+</sxh>
  
 Note that the last two lines of code (line 23-24) illustrate a way of converting the original list of tuples (''​classified_words''​) to a vertical list of tokens with NER labels by means of a for-loop. ​ Note that the last two lines of code (line 23-24) illustrate a way of converting the original list of tuples (''​classified_words''​) to a vertical list of tokens with NER labels by means of a for-loop. ​