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HeidelTime is a multilingual cross-domain temporal tagger that extracts temporal expressions from documents and normalizes them according to the TIMEX3 annotation standard.

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/*
 Copyright (C) 2010 by
 * 
 * 	Cam-Tu Nguyen 
 *  [email protected] or [email protected]
 *
 *  Xuan-Hieu Phan  
 *  [email protected] 
 *
 *  College of Technology, Vietnamese University, Hanoi
 * 	Graduate School of Information Sciences, Tohoku University
 *
 * JVnTextPro-v.2.0 is a free software; you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published
 * by the Free Software Foundation; either version 2 of the License,
 * or (at your option) any later version.
 *
 * JVnTextPro-v.2.0 is distributed in the hope that it will be useful, but
 * WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with  JVnTextPro-v.2.0); if not, write to the Free Software Foundation,
 * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA.
 */

package jmaxent;

import java.util.*;

// TODO: Auto-generated Javadoc
/**
 * The Class Observation.
 */
public class Observation {
    
    /** The original data. */
    public String originalData = "";
    
    /** The cps. */
    public int[] cps = null;
    
    /** The human label. */
    public int humanLabel = -1;
    
    /** The model label. */
    public int modelLabel = -1;
    
    //context predicate id representing the identity of current word
    //curWordCp == -1 means this word is not in the training data
    /** The cur word cp. */
    public int curWordCp = -1; 
    
    //curWordCp == -1 && dictLabel != -1, modelLabel = dictLabel
    /** The dict label. */
    public int dictLabel = -1;     
    
    /**
     * Instantiates a new observation.
     */
    public Observation() {
	// do nothing	
    }
    
    /**
     * Instantiates a new observation.
     *
     * @param cps the cps
     */
    public Observation(int[] cps) {
	this.cps = new int[cps.length];
	
	for (int i = 0; i < cps.length; i++) {
	    this.cps[i] = cps[i];
	}
    }
    
    /**
     * Instantiates a new observation.
     *
     * @param intCps the int cps
     */
    public Observation(List intCps) {
	this.cps = new int[intCps.size()];
	
	for (int i = 0; i < intCps.size(); i++) {
	    Integer intCp = (Integer)intCps.get(i);
	    
	    this.cps[i] = intCp.intValue();
	}
    }
    
    /**
     * Instantiates a new observation.
     *
     * @param humanLabel the human label
     * @param cps the cps
     */
    public Observation(int humanLabel, int[] cps) {
	this.humanLabel = humanLabel;
	this.cps = new int[cps.length];
	
	for (int i = 0; i < cps.length; i++) {
	    this.cps[i] = cps[i];
	}
    }    
    
    /**
     * To string.
     *
     * @param lbInt2Str the lb int2 str
     * @return the string
     */
    public String toString(Map lbInt2Str) {
	String res = originalData;

	String modelLabelStr = (String)lbInt2Str.get(new Integer(modelLabel));
	if (modelLabelStr != null) {
	    res += Option.labelSeparator + modelLabelStr;
	}
	
	return res;
    }
    
} // end of class Observation