Changes between Version 16 and Version 17 of private/NlpInPracticeCourse/NamedEntityRecognition

Timestamp:

Oct 9, 2017, 11:44:01 AM (5 years ago)

Author:

Ales Horak

Comment:

--

private/NlpInPracticeCourse/NamedEntityRecognition

@@ -56 +56 @@
 1. train the model using the default settings (cnec.prop), N.B. that the `convert_cnec_stanford.py` only recognizes PERSON, LOCATION and ORGANIZATION, you can extend the markup conversion later: 
 {{{
-java -cp stanford-ner.jar edu.stanford.nlp.ie.crf.CRFClassifier \
+java -cp stanford-ner-2017-06-09/stanford-ner.jar edu.stanford.nlp.ie.crf.CRFClassifier \
   -prop cnec.prop
 }}}
 1. convert the test data to the Stanford NER format: 
  {{{
-python convert_cnec_stanford.py named_ent_dtest.xml \
+python convert_cnec_stanford.py cnec2.0/data/xml/named_ent_dtest.xml \
   > named_ent_dtest.tsv
 }}}
 1. evaluate the model on `dtest`: 
 {{{
-java -cp stanford-ner.jar edu.stanford.nlp.ie.crf.CRFClassifier \
+java -cp stanford-ner-2017-06-09/stanford-ner.jar edu.stanford.nlp.ie.crf.CRFClassifier \
   -loadClassifier cnec-3class-model.ser.gz \
   -testFile named_ent_dtest.tsv
@@ -83 +83 @@
 10. evaluate the model on `dtest` with only NEs that are not present in the train data: 
  {{{
-java -cp stanford-ner.jar edu.stanford.nlp.ie.crf.CRFClassifier \
+java -cp stanford-ner-2017-06-09/stanford-ner.jar edu.stanford.nlp.ie.crf.CRFClassifier \
   -loadClassifier cnec-3class-model.ser.gz \
   -testFile named_ent_dtest_unknown.tsv
@@ -91 +91 @@
 11. test on your own input: 
  {{{
-java -mx600m -cp stanford-ner.jar edu.stanford.nlp.ie.crf.CRFClassifier \
+java -mx600m -cp stanford-ner-2017-06-09/stanford-ner.jar edu.stanford.nlp.ie.crf.CRFClassifier \
   -loadClassifier cnec-3class-model.ser.gz -textFile sample.txt
 }}}