modelbuilder-prototype/src/main/java/opennlp/modelbuilder/v2/Example.java

/*
 * Copyright 2013 The Apache Software Foundation.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package opennlp.modelbuilder.v2;

import java.util.HashMap;
import java.util.Map;
import opennlp.modelbuilder.v2.impls.FileKnownEntityProvider;
import opennlp.modelbuilder.v2.impls.FileModelValidatorImpl;
import opennlp.modelbuilder.v2.impls.FileSentenceProvider;
import opennlp.modelbuilder.v2.impls.ModelableImpl;

/**
 *
 * @author Owner
 */
public class Example {

  public static void main(String[] args) {

    SemiSupervisedModelGenerator modelGenerator = new GenericModelGenerator();
    //every component has a map as a place to recieve params
    //these are required for the current file-based impls
    Map<String, String> params = new HashMap<String, String>();
    params.put("knownentityfile", "C:\\apache\\entitylinker\\opennlp.geoentitylinker.countrycontext.txt");
    params.put("sentencesfile", "C:\\apache\\modelbuilder\\sentences.txt");
    params.put("knownentitytype", "location");
    params.put("blacklistfile", "C:\\apache\\modelbuilder\\blacklist.txt");
    params.put("modelablepath", "C:\\apache\\modelbuilder");

    /**
     * sentence providers feed this process with user data derived sentences
     * this impl just reads line by line through a file
     */
    SentenceProvider sentenceProvider = new FileSentenceProvider();
    sentenceProvider.setParameters(params);
    /**
     *KnownEntityProviders provide a seed list of known entities... such as Barack Obama for person, or Germany for location
     * obviously these would want to be prolific, non ambiguous names
     */
    KnownEntityProvider knownEntityProvider = new FileKnownEntityProvider();
    knownEntityProvider.setParameters(params);
    /**
     * ModelGenerationValidators try to weed out bad hits by the iterations of the name finder.
     * Since this is a recursive process, with each iteration the namefinder will get more and more greedy if bad entities are allowed in
     * this provides a mechanism for throwing out obviously bad hits.
     * A good impl may be to make sure a location is actually within a noun phrase etc...users can make this as specific as they need for their dat
     * and their use case
     */
    ModelGenerationValidator validator = new FileModelValidatorImpl();
    validator.setParameters(params);
    /**
     * Modelable's write and read the annotated sentences, as well as create and write the NER models
     */

    Modelable modelable = new ModelableImpl();
    modelable.setParameters(params);

    /**
     * the modelGenerator actually runs the process with a set number of iterations... could be better by actually calculating the
     * diff between runs and stopping based on a thresh, but for extrememly large sentence sets this may be too much.
     */
    modelGenerator.build(sentenceProvider, knownEntityProvider, validator, modelable, 2);

  }
}