Package opennlp.model

Examples of opennlp.model.Event

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      while ((line = reader.readLine()) != null) {
        String[] items = line.split("\\s+");
        String label = items[5];
        String[] context = { "verb=" + items[1], "noun=" + items[2],
            "prep=" + items[3], "prep_obj=" + items[4] };
        events.add(new Event(label, context));
      }
    }
    finally {
      in.close();
    }
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  public Event next() {
    while (next == null && this.ds.hasNext())
      next = createEvent((String)this.ds.nextToken());
   
    Event current = next;
    if (this.ds.hasNext()) {
      next = createEvent((String)this.ds.nextToken());
    }
    else {
      next = null;
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    if (lastSpace == -1)
      return null;
    else {
      String[] contexts = obs.substring(0,lastSpace).split("\\s+");
      float[] values = RealValueFileEventStream.parseContexts(contexts);
      return new Event(obs.substring(lastSpace+1),contexts,values);
    }
  }
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  public boolean hasNext() throws IOException {
    return stream.hasNext();
  }

  public Event next() throws IOException {
    Event event = stream.next();
   
    try {
      writer.write(event.toString());
      writer.write("\n");
    } catch (IOException e) {
      // TODO: Fix this, we need error handling in event streams
      e.printStackTrace();
    }
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          }
        }
      }
    }
    for (int ti = 0, tl = toks.size(); ti < tl; ti++) {
      chunkEvents.add(new Event(preds.get(ti), chunkerContextGenerator.getContext(ti, toks.toArray(new String[toks.size()]), tags.toArray(new String[tags.size()]), preds.toArray(new String[preds.size()]))));
    }
  }
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          preds.add(tok.getType());
        }
      }
    }
    for (int ti = 0, tl = toks.size(); ti < tl; ti++) {
      tagEvents.add(new Event(preds.get(ti), tagContextGenerator.getContext(ti,
          toks.toArray(new String[toks.size()]), preds.toArray(new String[preds.size()]), null)));
    }
  }
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    return eventStream.hasNext();
  }

  public Event next() throws IOException {
   
    Event event = eventStream.next();
   
    try {
      digest.update(event.toString().getBytes("UTF-8"));
    }
    catch (UnsupportedEncodingException e) {
      throw new IllegalStateException("UTF-8 encoding is not available!");
    }
   
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  }

  public void addEvent(MentionContext ec) {
    List<String> features = getFeatures(ec);
    if (-1 == ec.getId()) {
      events.add(new Event(MaxentResolver.SAME, features.toArray(new String[features.size()])));
    }
    else {
      events.add(new Event(MaxentResolver.DIFF, features.toArray(new String[features.size()])));
    }
  }
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    if (ResolverMode.TRAIN == mode) {
      System.err.println(this +" referential");
      if (debugOn) {
        FileWriter writer = new FileWriter(modelName+".events");
        for (Iterator<Event> ei=events.iterator();ei.hasNext();) {
          Event e = ei.next();
          writer.write(e.toString()+"\n");
        }
        writer.close();
      }
      (new SuffixSensitiveGISModelWriter(GIS.trainModel(new CollectionEventStream(events),100,10),new File(modelName+modelExtension))).persist();
    }
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  private void addEvent(boolean same, Context np1, Context np2) {
    if (same) {
      List<String> feats = getFeatures(np1, np2);
      //System.err.println(SAME+" "+np1.headTokenText+" ("+np1.id+") -> "+np2.headTokenText+" ("+np2.id+") "+feats);
      events.add(new Event(SAME, feats.toArray(new String[feats.size()])));
    }
    else {
      List<String> feats = getFeatures(np1, np2);
      //System.err.println(DIFF+" "+np1.headTokenText+" ("+np1.id+") -> "+np2.headTokenText+" ("+np2.id+") "+feats);
      events.add(new Event(DIFF, feats.toArray(new String[feats.size()])));
    }
  }
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Related Classes of opennlp.model.Event

  • com.tamingtext.qa.AnswerTypeEventStream
  • edu.washington.cs.knowitall.extractor.conf.opennlp.OpenNlpDataSet
  • opennlp.maxent.BasicEventStream
  • opennlp.maxent.quasinewton.QNTrainerTest
  • opennlp.maxent.RealBasicEventStream
  • opennlp.model.HashSumEventStream
  • opennlp.PrepAttachDataUtil
  • opennlp.tools.chunker.ChunkerEventStream
  • opennlp.tools.coref.resolver.DefaultNonReferentialResolver
  • opennlp.tools.coref.resolver.MaxentResolver
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