Package opennlp.maxent

Examples of opennlp.maxent.Event

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          outcome = ParserME.CONT + type;
        }
        //System.err.println("parserEventStream.addParseEvents: chunks["+ci+"]="+c+" label="+outcome);
        c.setLabel(outcome);
        if (etype == EventTypeEnum.BUILD) {
          parseEvents.add(new Event(outcome, bcg.getContext(chunks, ci)));
        }
        int start = ci - 1;
        while (start >= 0 && chunks[start].getParent() == parent) {
          start--;
        }
        if (lastChild(c, parent)) {
          if (etype == EventTypeEnum.CHECK) {
            parseEvents.add(new Event(ParserME.COMPLETE, kcg.getContext( chunks, type, start + 1, ci)));
          }
          //perform reduce
          int reduceStart = ci;
          while (reduceStart >=0 && chunks[reduceStart].getParent() == parent) {
            reduceStart--;
          }
          reduceStart++;
          chunks = reduceChunks(chunks,ci,parent);
          ci=reduceStart-1; //ci will be incremented at end of loop
        }
        else {
          if (etype == EventTypeEnum.CHECK) {
            parseEvents.add(new Event(ParserME.INCOMPLETE, kcg.getContext(chunks, type, start + 1, ci)));
          }
        }
      }
      ci++;
    }
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          }
        }
      }
    }
    for (int ti = 0, tl = toks.size(); ti < tl; ti++) {
      chunkEvents.add(new Event((String) preds.get(ti), ccg.getContext(ti, toks.toArray(), (String[]) tags.toArray(new String[tags.size()]), (String[]) 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((String) preds.get(ti), tcg.getContext(ti, toks.toArray(), (String[]) preds.toArray(new String[preds.size()]), null)));
    }
  }
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  }
 
  public void addEvent(MentionContext ec) {
    List features = getFeatures(ec);
    if (-1 == ec.getId()) {
      events.add(new Event(MaxentResolver.SAME, (String[]) features.toArray(new String[features.size()])));
    }
    else {
      events.add(new Event(MaxentResolver.DIFF, (String[]) 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 ei=events.iterator();ei.hasNext();) {
          Event e = (Event) 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 feats = getFeatures(np1, np2);
      //System.err.println(SAME+" "+np1.headTokenText+" ("+np1.id+") -> "+np2.headTokenText+" ("+np2.id+") "+feats);
      events.add(new Event(SAME, (String[]) feats.toArray(new String[feats.size()])));
    }
    else {
      List feats = getFeatures(np1, np2);
      //System.err.println(DIFF+" "+np1.headTokenText+" ("+np1.id+") -> "+np2.headTokenText+" ("+np2.id+") "+feats);
      events.add(new Event(DIFF, (String[]) feats.toArray(new String[feats.size()])));
    }
  }
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   */
  public void trainModel() throws IOException {
    if (debugOn) {
      FileWriter writer = new FileWriter(modelName+".events");
      for (Iterator ei=events.iterator();ei.hasNext();) {
        Event e = (Event) 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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    return features;
  }

  private void addEvent(String outcome, Context np1) {
    List feats = getFeatures(np1);
    events.add(new Event(outcome, (String[]) feats.toArray(new String[feats.size()])));
  }
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        isEntity = "F";
      }
      List<String> features = fe.getFeatures(entity);
      String type = entity.getType();
      if(!eventsByType.containsKey(type)) eventsByType.put(type, new ArrayList<Event>());
      eventsByType.get(type).add(new Event(isEntity, features.toArray(new String[0])));
    }
  }
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    tagSet.add(thisTag);
    if(useUber) {
      features.add("$$prevTag=" + prevTag);
    }
    String [] c = features.toArray(new String[0]);
    Event ev = new Event(thisTag, c);
    List<Event> evs = evsByPrev.get(prevTag);
    if(evs == null) {
      evs = new ArrayList<Event>();
      evsByPrev.put(prevTag, evs);
    }
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Related Classes of opennlp.maxent.Event

  • opennlp.tools.chunker.ChunkerEventStream
  • opennlp.tools.coref.resolver.DefaultNonReferentialResolver
  • opennlp.tools.coref.resolver.MaxentResolver
  • opennlp.tools.coref.sim.GenderModel
  • opennlp.tools.coref.sim.NumberModel
  • opennlp.tools.coref.sim.SimilarityModel
  • opennlp.tools.namefind.NameFinderEventStream
  • opennlp.tools.parser.ParserEventStream
  • opennlp.tools.postag.POSEventCollector
  • opennlp.tools.tokenize.TokEventCollector
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