如何对自定义NameFinder模型进行OpenNLP培训？

Question

result for roll number 1304510020.
result for roll-number 1304510020.
result for rollnumber 1304510020.
result of rollnumber 1304510020.
result of roll number 1304510020.
result of roll-number 1304510020.
roll number 1304510020 result.
rollnumber 1304510020 result.
roll-number 1304510020 result.
show result of roll number 1304510020.
show result of rollnumber 1304510020.
show result of roll-number 1304510020.
show my result for 1304510020.
result of 1304510020.

这是我的培训代码

package nlpParser;

import java.io.BufferedOutputStream;
import java.io.FileInputStream;
import java.io.FileOutputStream;
import java.io.IOException;
import java.io.InputStream;
import java.nio.charset.Charset;

import opennlp.tools.namefind.NameFinderME;
import opennlp.tools.namefind.NameSample;
import opennlp.tools.namefind.NameSampleDataStream;
import opennlp.tools.namefind.TokenNameFinderFactory;
import opennlp.tools.namefind.TokenNameFinderModel;
import opennlp.tools.util.InputStreamFactory;
import opennlp.tools.util.ObjectStream;
import opennlp.tools.util.PlainTextByLineStream;
import opennlp.tools.util.TrainingParameters;
public class Trainer {
	// training data set
    static String trainingPath = 
    		"C:\\Users\\MujeebulHasan\\Desktop\\Project\\hbtu\\hbtuaiagent\\Source Code\\parser\\training\\";
    
    public static void main(String[] args) throws IOException {

    	String[] entities = new String[]{"rollnumber","result"};
    	String[] pathsOfTraingFile = new String[]{"rollnumber\\rollnumber.train","result\\result.train"};
    	String[] pathsOfTrainedFile = new String[]{"rollnumber\\rollnumber.bin","result\\result.bin"};
    	
    	for(int i = 0; i < entities.length; i++){
    		final int j = i;
		    InputStreamFactory isf = new InputStreamFactory() {
		        public InputStream createInputStream() throws IOException {
		            return new FileInputStream(trainingPath+pathsOfTraingFile[j]);
		        }
		    };
		    Charset charset = Charset.forName("UTF-8");
		    ObjectStream<String> lineStream = new PlainTextByLineStream(isf, charset);
		    ObjectStream<NameSample> sampleStream = new NameSampleDataStream(lineStream);
		    TokenNameFinderModel model;
		    TokenNameFinderFactory nameFinderFactory = new TokenNameFinderFactory();
		    try {
		        model = NameFinderME.train("en", entities[i], sampleStream, TrainingParameters.defaultParams(),
		                nameFinderFactory);
		    } finally {
		        sampleStream.close();
		    }
		    BufferedOutputStream modelOut = null;
		    try {
		        modelOut = new BufferedOutputStream(new FileOutputStream(trainingPath+pathsOfTrainedFile[i]));
		        model.serialize(modelOut);
		    } finally {
		        if (modelOut != null)
		            modelOut.close();
		    }
    	}
    }
}

滚轮编号。火车

result for roll number <START:rollnumber> 1304510020 <END> .
result for roll-number <START:rollnumber> 1304510020 <END> .
result for rollnumber <START:rollnumber> 1304510020 <END> .
result for roll <START:rollnumber> 1304510020 <END> .
result of rollnumber <START:rollnumber> 1304510020 <END> .
result of roll number <START:rollnumber> 1304510020 <END> .
result of roll-number <START:rollnumber> 1304510020 <END> .
result of roll <START:rollnumber> 1304510020 <END> .
roll number <START:rollnumber> 1304510020 <END> result.
rollnumber <START:rollnumber> 1304510020 <END> result.
roll-number <START:rollnumber> 1304510020 <END> result.
roll <START:rollnumber> 1304510020 <END> result.
show result of roll number <START:rollnumber> 1304510020 <END> .
show result of rollnumber <START:rollnumber> 1304510020 <END> .
show result of roll-number <START:rollnumber> 1304510020 <END> .
show result of roll <START:rollnumber> 1304510020 <END> .
show my result for <START:rollnumber> 1304510020 <END> .
result of <START:rollnumber> 1304510020 <END> .
result for <START:rollnumber> 1304510020 <END> .
what is my result for rollnumber <START:rollnumber> 1304510020 <END> .
what is my result of rollnumber <START:rollnumber> 1304510020 <END> .
what is my result for roll <START:rollnumber> 1304510020 <END> .

结果训练

<START:result> result <END> for roll number 1304510020.
<START:result> result <END> for roll-number 1304510020.
<START:result> result <END> for rollnumber 1304510020.
<START:result> result <END> of rollnumber 1304510020.
<START:result> result <END> of roll number 1304510020.
<START:result> result <END> of roll-number 1304510020.
roll number 1304510020 <START:result> result <END> .
rollnumber 1304510020 <START:result> result <END> .
roll-number 1304510020 <START:result> result <END> .
show <START:result> result <END> of roll number 1304510020.
show <START:result> result <END> of rollnumber 1304510020.
show <START:result> result <END> of roll-number 1304510020.
show my <START:result> result <END> for 1304510020.
<START:result> result <END> of 1304510020.

当我使用这段代码测试它时。

package nlpParser;

import java.io.FileInputStream;
import java.io.IOException;
import java.io.InputStream;
import java.util.Scanner;

import opennlp.tools.namefind.NameFinderME;
import opennlp.tools.namefind.TokenNameFinderModel;
import opennlp.tools.util.Span;

public class GetEntities {
	public static void main(String[] args) throws IOException {
		Scanner sc = new Scanner(System.in);
		String query ="";
		GetEntities obj = new GetEntities();
		while((query = sc.nextLine()) != " "){
			obj.parse(query);
		}
		sc.close();
	}
	public void parse(String query) throws IOException{
		String[] entities = new String[]{"rollnumber","result"};
		   String[] pathsOfTrainedFile = new String[]{"rollnumber\\rollnumber.bin","result\\result.bin"};
		   
		   for(int i = 0 ; i < entities.length; i++){
			   //Loading the NER model       
			   InputStream inputStream = new 
			   FileInputStream("C:\\Users\\MujeebulHasan\\Desktop\\Project\\hbtu\\hbtuaiagent\\Source Code\\parser\\training\\"+pathsOfTrainedFile[i]); 
			   TokenNameFinderModel model = new TokenNameFinderModel(inputStream);
			   //Instantiating the NameFinder class 
			   NameFinderME nameFinder = new NameFinderME(model); 
	    	   
				   //Finding the names in the sentence 
	    		   System.out.println("Processing query... ");
	    		   System.out.print("Query = "+query);
				   query = query.replace(".", "");
				   String[] sentence = query.split(" ");
				   System.out.println();
				   System.out.println("RESULT :");
				   Span nameSpans[] = nameFinder.find(sentence); 
				   //Printing the spans of the names in the sentence 
				   for(Span s: nameSpans) {
					   System.out.println(s.toString());
					   System.out.println(sentence[s.getStart()]);
				   }
			   }
		   }
}

给出了如下结果。有些时候是错的。

result of roll number 1304510020
Processing query... 
Query = result of roll number 1304510020
RESULT :
Processing query... 
Query = result of roll number 1304510020
RESULT :
[0..1) result
result
show result for roll number 1304510020
Processing query... 
Query = show result for roll number 1304510020
RESULT :
Processing query... 
Query = show result for roll number 1304510020
RESULT :
[1..2) result
result
result for rollnumber 1304510020
Processing query... 
Query = result for rollnumber 1304510020
RESULT :
[3..4) rollnumber
1304510020
Processing query... 
Query = result for rollnumber 1304510020
RESULT :
[0..1) result
result
result 1304510020
Processing query... 
Query = result 1304510020
RESULT :
Processing query... 
Query = result 1304510020
RESULT :
[0..1) result
result
1304510020 result
Processing query... 
Query = 1304510020 result
RESULT :
Processing query... 
Query = 1304510020 result
RESULT :
[1..2) result
result

Answer 1

发生这种事。由于您的训练数据的大小。根据OpenNLP文档，训练数据中必须有大约15,000行，才能获得好的结果。

如果您没有足够的数据，您可以简单地在您的情况下使用正则表达式，这比所有这些都容易得多。

如果您愿意制作一个更大的训练数据集，您可以遵循这个规则，或者再次使用RegEX来标记您的非常大的语料库。