update

.gitignore

@@ -1,2 +1,3 @@
 */.DS_Store
-.DS_Store
+.DS_Store
+.idea/

README.md

@@ -33,22 +33,22 @@ It looks like a portion of [MSRA corpus](http://sighan.cs.uchicago.edu/bakeoff20
 
 ### test
 
-`python main.py --mode=test --demo_model=1521016137`
+`python main.py --mode=test --demo_model=1521112368`
 
-Please set the parameter `--demo_model` to the model which you want to test. `1521016137` is the model trained by me. 
+Please set the parameter `--demo_model` to the model which you want to test. `1521112368` is the model trained by me. 
 
 An official evaluation tool: [here (click 'Instructions')](http://sighan.cs.uchicago.edu/bakeoff2006/)
 
 My test performance:
 
 | P     | R     | F     | F (PER)| F (LOC)| F (ORG)|
 | :---: | :---: | :---: | :---: | :---: | :---: |
-| 0.8979 | 0.8690 | 0.8832 | 0.8692 | 0.9088 | 0.8493
+| 0.8945 | 0.8752 | 0.8847 | 0.8688 | 0.9118 | 0.8515
 
 
 ### demo
 
-`python main.py --mode=demo --demo_model=1521016137`
+`python main.py --mode=demo --demo_model=1521112368`
 
 You can input one Chinese sentence and the model will return the recognition result:
 

data.py

@@ -81,6 +81,8 @@ def sentence2id(sent, word2id):
     for word in sent:
         if word.isdigit():
             word = '<NUM>'
+        elif ('\u0041' <= word <= '\u005a') or ('\u0061' <= word <= '\u007a'):
+            word = '<ENG>'
         if word not in word2id:
             word = '<UNK>'
         sentence_id.append(word2id[word])