opennlp.tools.cmdline.tokenizer.TokenizerMEEvaluatorTool Maven / Gradle / Ivy
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* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You 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.tools.cmdline.tokenizer;
import java.io.IOException;
import opennlp.tools.cmdline.AbstractEvaluatorTool;
import opennlp.tools.cmdline.TerminateToolException;
import opennlp.tools.cmdline.params.EvaluatorParams;
import opennlp.tools.cmdline.tokenizer.TokenizerMEEvaluatorTool.EvalToolParams;
import opennlp.tools.tokenize.TokenSample;
import opennlp.tools.tokenize.TokenizerEvaluationMonitor;
import opennlp.tools.tokenize.TokenizerEvaluator;
import opennlp.tools.tokenize.TokenizerModel;
public final class TokenizerMEEvaluatorTool
extends AbstractEvaluatorTool {
interface EvalToolParams extends EvaluatorParams {
}
public TokenizerMEEvaluatorTool() {
super(TokenSample.class, EvalToolParams.class);
}
public String getShortDescription() {
return "evaluator for the learnable tokenizer";
}
public void run(String format, String[] args) {
super.run(format, args);
TokenizerModel model = new TokenizerModelLoader().load(params.getModel());
TokenizerEvaluationMonitor misclassifiedListener = null;
if (params.getMisclassified()) {
misclassifiedListener = new TokenEvaluationErrorListener();
}
TokenizerEvaluator evaluator = new TokenizerEvaluator(
new opennlp.tools.tokenize.TokenizerME(model), misclassifiedListener);
System.out.print("Evaluating ... ");
try {
evaluator.evaluate(sampleStream);
} catch (IOException e) {
System.err.println("failed");
throw new TerminateToolException(-1, "IO error while reading test data: " + e.getMessage(), e);
} finally {
try {
sampleStream.close();
} catch (IOException e) {
// sorry that this can fail
}
}
System.out.println("done");
System.out.println();
System.out.println(evaluator.getFMeasure());
}
}