Changes between Version 18 and Version 19 of private/NlpInPracticeCourse/NamedEntityRecognition

Timestamp:

Oct 2, 2019, 10:05:58 AM (5 years ago)

Author:

Zuzana Nevěřilová

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-2017-06-09/stanford-ner.jar \
+java -cp stanford-ner-2018-10-16/stanford-ner.jar \
   edu.stanford.nlp.ie.crf.CRFClassifier \
   -prop cnec.prop
@@ -67 +67 @@
 1. evaluate the model on `dtest`: 
 {{{
-java -cp stanford-ner-2017-06-09/stanford-ner.jar \
+java -cp stanford-ner-2018-10-16/stanford-ner.jar \
   edu.stanford.nlp.ie.crf.CRFClassifier \
   -loadClassifier cnec-3class-model.ser.gz \
@@ -85 +85 @@
 10. evaluate the model on `dtest` with only NEs that are not present in the train data: 
  {{{
-java -cp stanford-ner-2017-06-09/stanford-ner.jar \
+java -cp stanford-ner-2018-10-16/stanford-ner.jar \
   edu.stanford.nlp.ie.crf.CRFClassifier \
   -loadClassifier cnec-3class-model.ser.gz \
@@ -94 +94 @@
 11. test on your own input: 
  {{{
-java -mx600m -cp stanford-ner-2017-06-09/stanford-ner.jar \
+java -mx600m -cp stanford-ner-2018-10-16/stanford-ner.jar \
   edu.stanford.nlp.ie.crf.CRFClassifier \
   -loadClassifier cnec-3class-model.ser.gz -textFile sample.txt