title: Named Entity Recognition using WEKA
body: <p>I am new to WEKA and I want to ask you few questions regarding WEKA.
  I had follow this tutorial (<a href="http://www.linguisticsweb.org/doku.php?id=linguisticsweb:tutorials:linguistics_tutorials_linguistic_processing_scenarios:named_entity_recognition" rel="nofollow">Named Entity Recognition using WEKA</a>).</p>
  
  <p>But I am really confusing and have no idea at all.</p>
  
  <ol>
  <li>Is it possible if I want to filter the string by phrase not word/token?</li>
  </ol>
  
  <p>For example in my .ARFF file:</p>
  
  <pre><code>  @attribute text string
    @attribute tag {CC, CD, DT, EX, FW, IN, JJ, JJR, JJS, LS, MD, NN, NNS, NNP, NNPS, PDT, POS, PRP, PRP$, RB, RBR, RBS, RP, SYM, TO, UH, VB, VBD , VBG, VBN , VBP, VBZ, WDT, WP, WP$, WRB, ,, ., :}
    @attribute capital {Y, N}
    @attribute chunked {B-NP, I-NP, B-VP, I-VP, B-PP, I-PP, B-ADJP, B-ADVP , B-SBAR, B-PRT, O-Punctuation}
    @attribute @@class@@ {B-PER, I-PER, B-ORG, I-ORG, B-NUM, I-NUM, O, B-LOC, I-LOC}
  
    @data
    'Wanna',NNP,Y,B-NP,O
    'be',VB,N,B-VP,O
    'like',IN,N,B-PP,O
    'New',NNP,Y,B-NP,B-LOC
    'York',NNP,Y,I-NP,I-LOC
     '?',.,N,O-Punctuation,O
  </code></pre>
  
  <p>So, when I filtered the String, it tokenized the string into word but what I want is, I want to tokenize/filter the string according to the phrase. For example extract the phrase "New York" not "New" and "York" according to the chunked attributes.</p>
  
  <p>"B-NP" means start phrase and "I-NP" means next phrase (the middle or  end of the phrase).</p>
  
  <ol start="2">
  <li>How can i show the result for the classify class for example:</li>
  </ol>
  
  <p>B-PER and I-PER to the class name PERSON?</p>
  
  <pre><code>                 TP Rate   FP Rate   Precision   Recall  F-Measure   ROC Area  Class
                      0         0.021      0         0         0          0.768    B-PER
                      1         0.084      0.333     1         0.5        0.963    I-PER
                    0.167     0.054      0.167     0.167     0.167      0.313    B-ORG
                      0         0          0         0         0          0.964    I-ORG
                      0         0          0         0         0          0.281    B-NUM
                      0         0          0         0         0          0.148    I-NUM
                      0.972     0.074      0.972     0.972     0.972      0.949    O
                      0.875     0          1         0.875     0.933      0.977    B-LOC
                      0         0          0         0         0          0.907    I-LOC
  </code></pre>
  
  <p>Weighted Avg.    0.828     0.061      0.811     0.828     0.813      0.894</p>