title: StanfordCoreNLPClient don't work as expected on sentiment analysis
body: <p>Stanford CoreNLP version 3.9.1</p>
  
  <p>I have a problem getting <code>StanfordCoreNLPClient</code> work the same way as <code>StanfordCoreNLP</code> when doing sentiment analysis.</p>
  
  <pre><code>public class Test {
  
    public static void main(String[] args) {
      String text = "This server doesn't work!";
  
      Properties props = new Properties();
      props.setProperty("annotators", "tokenize, ssplit, pos, lemma, ner, parse, sentiment");
  
      //If I uncomment this line, and comment out the next one, it works                            
      //StanfordCoreNLP pipeline = new StanfordCoreNLP(props);
      StanfordCoreNLPClient pipeline = new StanfordCoreNLPClient(props, "http://localhost", 9000, 2);
  
      Annotation annotation = new Annotation(text);
      pipeline.annotate(annotation);
      CoreDocument document = new CoreDocument(annotation);           
      CoreSentence sentence = document.sentences().get(0);
  
      //outputs null when using StanfordCoreNLPClient
      System.out.println(RNNCoreAnnotations.getPredictions(sentence.sentimentTree())); 
  
      //throws null pointer when using StanfordCoreNLPClien (reason of course is that it uses the same method I called above, I assume)   
      System.out.println(RNNCoreAnnotations.getPredictionsAsStringList(sentence.sentimentTree()));  
  
  }
  </code></pre>
  
  <p>}</p>
  
  <p>Output using <code>StanfordCoreNLPClient pipeline = new StanfordCoreNLPClient(props, "http://localhost", 9000, 2)</code>:</p>
  
  <pre><code> null
   Exception in thread "main" java.lang.NullPointerException
  at edu.stanford.nlp.neural.rnn.RNNCoreAnnotations.getPredictionsAsStringList(RNNCoreAnnotations.java:68)
  at tomkri.mastersentimentanalysis.preprocessing.Test.main(Test.java:35)
  </code></pre>
  
  <p>Output using <code>StanfordCoreNLP pipeline = new StanfordCoreNLP(props)</code>:</p>
  
  <pre><code>     Type = dense , numRows = 5 , numCols = 1
       0.127  
       0.599  
       0.221  
       0.038  
       0.015  
  
       [0.12680336652661395, 0.5988695516384742, 0.22125584263055106, 0.03843574738131668, 0.014635491823044227]
  </code></pre>
  
  <p>Other annotations than sentiment works in both cases (at least those I have tried).</p>
  
  <p>The server starts fine, and I am able to use from my web browser. When using it there I also get output of sentiment scores (on each subtree in the parse) in json format.</p>