OpenNLP小记（利用OpenNLP寻找人名）

利用OpenNLP进行人名命名实体识别，代码来源于《驾驭文本》第五章。

import java.io.File;
import java.io.FileInputStream;

import opennlp.tools.namefind.NameFinderME;
import opennlp.tools.namefind.TokenNameFinderModel;
import opennlp.tools.tokenize.SimpleTokenizer;
import opennlp.tools.tokenize.Tokenizer;
import opennlp.tools.util.Span;

public class NamedEntityExtraction {
	public static void main(String[] args) throws Exception {
		String[] sentences = {
				"Former first lady Nancy Reagan was taken to a " + "suburban Los Angeles "
						+ "hospital \"as a precaution\" Sunday after a fall at " + "her home, an " + "aide said. ",
				"The 86-year-old Reagan will remain overnight for "
						+ "observation at a hospital in Santa Monica, California, " + "said Joanne "
						+ "Drake, chief of staff for the Reagan Foundation." };//两句话
		NameFinderME finder = new NameFinderME(new TokenNameFinderModel(
				new FileInputStream(new File(System.getProperty("model.dir"), "./nlpbin/en-ner-person.bin"))));//在http://opennlp.sourceforge.net/models-1.5/ 下载en-ner-person.bin
		Tokenizer tokenizer = SimpleTokenizer.INSTANCE;//初始化简单切词（也就是按空格切词）
		for (int si = 0; si < sentences.length; si++) {
			String[] tokens = tokenizer.tokenize(sentences[si]);//第一句话[Former, first, lady, Nancy, Reagan, was, taken, to, a, suburban, Los, Angeles, hospital, ", as, a, precaution, ", Sunday, after, a, fall, at, her, home, ,, an, aide, said, .]
			//第二句话[The, 86, -, year, -, old, Reagan, will, remain, overnight, for, observation, at, a, hospital, in, Santa, Monica, ,, California, ,, said, Joanne, Drake, ,, chief, of, staff, for, the, Reagan, Foundation, .]
			Span[] names = finder.find(tokens);
			displayNames(names, tokens);
		}
		finder.clearAdaptiveData();
	}

	public static void displayNames(Span[] names, String[] tokens) {
		for (int si = 0; si < names.length; si++) {
			StringBuilder cb = new StringBuilder();
			for (int ti = names[si].getStart(); ti < names[si].getEnd(); ti++) {
				cb.append(tokens[ti]).append(" ");
			}
			System.out.println(cb.substring(0, cb.length() - 1));
			System.out.print("\tstart: " + names[si].getStart());
			System.out.println("\tend: " + names[si].getEnd());//输出实体的起止位置
			System.out.println("\ttype: " + names[si].getType());//输出实体的类型type
			System.out.println("\tprob: " + names[si].getProb());//输出实体的概率prob
		}
	}
}

span包含了这么几个属性：start（该实体的起始位置），end（该实体的终止位置），prob（可能性，实体的概率），还有type（实体的类型）。

输出结果如下：

Nancy Reagan
	start: 3	end: 5
	type: person
	prob: 0.9704748832886989
Reagan
	start: 6	end: 7
	type: person
	prob: 0.9996172457889334
Joanne Drake
	start: 22	end: 24
	type: person
	prob: 0.9929295961937021
Reagan
	start: 30	end: 31
	type: person
	prob: 0.9976318413669909