对于那些不想从源代码重新编译默认CoreNLP的人。你可以简单地创建你自己的类并从那里实现它。样本如下：
import java.io.IOException;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.Iterator;
import java.util.List;
import java.util.Map;
import java.util.Properties;
import java.util.logging.Level;
import java.util.logging.Logger;
import edu.stanford.nlp.ie.machinereading.GenericDataSetReader;
import edu.stanford.nlp.ie.machinereading.structure.AnnotationUtils;
import edu.stanford.nlp.ie.machinereading.structure.EntityMention;
import edu.stanford.nlp.ie.machinereading.structure.ExtractionObject;
import edu.stanford.nlp.ie.machinereading.structure.MachineReadingAnnotations;
import edu.stanford.nlp.ie.machinereading.structure.RelationMention;
import edu.stanford.nlp.ie.machinereading.structure.Span;
import edu.stanford.nlp.io.IOUtils;
import edu.stanford.nlp.ling.CoreAnnotations;
import edu.stanford.nlp.ling.CoreLabel;
import edu.stanford.nlp.pipeline.Annotation;
import edu.stanford.nlp.pipeline.StanfordCoreNLP;
import edu.stanford.nlp.trees.Tree;
import edu.stanford.nlp.util.StringUtils;
/**
* A Reader designed for the relation extraction data studied in Dan Roth and Wen-tau Yih,
* A Linear Programming Formulation for Global Inference in Natural Language Tasks. CoNLL 2004.
* The format is a somewhat ad-hoc tab-separated value file format.
*
* @author Mihai, David McClosky, and agusev
* @author Sonal Gupta ([email protected])
*/
public class TestReader extends GenericDataSetReader {
public TestReader() {
super(null, true, true, true);
// change the logger to one from our namespace
logger = Logger.getLogger(TestReader.class.getName());
// run quietly by default
logger.setLevel(Level.SEVERE);
}
@Override
public Annotation read(String path) throws IOException {
Annotation doc = new Annotation("");
logger.info("Reading file: " + path);
// Each iteration through this loop processes a single sentence along with any relations in it
for (Iterator<String> lineIterator = IOUtils.readLines(path).iterator(); lineIterator.hasNext();) {
Annotation sentence = readSentence(path, lineIterator);
AnnotationUtils.addSentence(doc, sentence);
}
return doc;
}
private boolean warnedNER; // = false;
private String getNormalizedNERTag(String ner) {
if (ner.equalsIgnoreCase("O")) {
return "O";
} else if (ner.equalsIgnoreCase("Peop")) {
return "PERSON";
} else if (ner.equalsIgnoreCase("LOCATION")) {
return "LOCATION";
} else if(ner.equalsIgnoreCase("Organization")) {
return "ORGANIZATION";
} else if(ner.equalsIgnoreCase("Other")) {
return "OTHER";
} else {
if (! warnedNER) {
warnedNER = true;
logger.warning("This file contains NER tags not in the original Roth/Yih dataset, e.g.: " + ner);
}
}
throw new RuntimeException("Cannot normalize ner tag " + ner);
}
private Annotation readSentence(String docId, Iterator<String> lineIterator) {
Annotation sentence = new Annotation("");
sentence.set(CoreAnnotations.DocIDAnnotation.class, docId);
sentence.set(MachineReadingAnnotations.EntityMentionsAnnotation.class, new ArrayList<>());
// we'll need to set things like the tokens and textContent after we've
// fully read the sentence
// contains the full text that we've read so far
StringBuilder textContent = new StringBuilder();
int tokenCount = 0; // how many tokens we've seen so far
List<CoreLabel> tokens = new ArrayList<>();
// when we've seen two blank lines in a row, this sentence is over (one
// blank line separates the sentence and the relations
int numBlankLinesSeen = 0;
String sentenceID = null;
// keeps tracks of entities we've seen so far for use by relations
Map<String, EntityMention> indexToEntityMention = new HashMap<>();
while (lineIterator.hasNext() && numBlankLinesSeen < 2) {
String currentLine = lineIterator.next();
currentLine = currentLine.replace("COMMA", ",");
List<String> pieces = StringUtils.split(currentLine);
String identifier;
int size = pieces.size();
switch (size) {
case 1: // blank line between sentences or relations
numBlankLinesSeen++;
break;
case 3: // relation
String type = pieces.get(2);
List<ExtractionObject> args = new ArrayList<>();
EntityMention entity1 = indexToEntityMention.get(pieces.get(0));
EntityMention entity2 = indexToEntityMention.get(pieces.get(1));
args.add(entity1);
args.add(entity2);
Span span = new Span(entity1.getExtentTokenStart(), entity2
.getExtentTokenEnd());
// identifier = "relation" + sentenceID + "-" + sentence.getAllRelations().size();
identifier = RelationMention.makeUniqueId();
RelationMention relationMention = new RelationMention(identifier,
sentence, span, type, null, args);
AnnotationUtils.addRelationMention(sentence, relationMention);
break;
case 9: // token
/*
* Roth token lines look like this:
*
* 19 Peop 9 O NNP/NNP Jamal/Ghosheh O O O
*/
// Entities may be multiple words joined by '/'; we split these up
List<String> words = StringUtils.split(pieces.get(5), "/");
//List<String> postags = StringUtils.split(pieces.get(4),"/");
String text = StringUtils.join(words, " ");
identifier = "entity" + pieces.get(0) + '-' + pieces.get(2);
String nerTag = getNormalizedNERTag(pieces.get(1)); // entity type of the word/expression
if (sentenceID == null)
sentenceID = pieces.get(0);
if (!nerTag.equals("O")) {
Span extentSpan = new Span(tokenCount, tokenCount + words.size());
// Temporarily sets the head span to equal the extent span.
// This is so the entity has a head (in particular, getValue() works) even if preprocessSentences isn't called.
// The head span is later modified if preprocessSentences is called.
EntityMention entity = new EntityMention(identifier, sentence,
extentSpan, extentSpan, nerTag, null, null);
AnnotationUtils.addEntityMention(sentence, entity);
// we can get by using these indices as strings since we only use them
// as a hash key
String index = pieces.get(2);
indexToEntityMention.put(index, entity);
}
// int i =0;
for (String word : words) {
CoreLabel label = new CoreLabel();
label.setWord(word);
//label.setTag(postags.get(i));
label.set(CoreAnnotations.TextAnnotation.class, word);
label.set(CoreAnnotations.ValueAnnotation.class, word);
// we don't set TokenBeginAnnotation or TokenEndAnnotation since we're
// not keeping track of character offsets
tokens.add(label);
// i++;
}
textContent.append(text);
textContent.append(' ');
tokenCount += words.size();
break;
}
}
sentence.set(CoreAnnotations.TextAnnotation.class, textContent.toString());
sentence.set(CoreAnnotations.ValueAnnotation.class, textContent.toString());
sentence.set(CoreAnnotations.TokensAnnotation.class, tokens);
sentence.set(CoreAnnotations.SentenceIDAnnotation.class, sentenceID);
return sentence;
}
/*
* Gets the index of an object in a list using == to test (List.indexOf uses
* equals() which could be problematic here)
*/
private static <X> int getIndexByObjectEquality(List<X> list, X obj) {
for (int i = 0, sz = list.size(); i < sz; i++) {
if (list.get(i) == obj) {
return i;
}
}
return -1;
}
/*
* Sets the head word and the index for an entity, given the parse tree for
* the sentence containing the entity.
*
* This code is no longer used, but I've kept it around (at least for now) as
* reference when we modify preProcessSentences().
*/
@SuppressWarnings("unused")
private void setHeadWord(EntityMention entity, Tree tree) {
List<Tree> leaves = tree.getLeaves();
Tree argRoot = tree.joinNode(leaves.get(entity.getExtentTokenStart()),
leaves.get(entity.getExtentTokenEnd()));
Tree headWordNode = argRoot.headTerminal(headFinder);
int headWordIndex = getIndexByObjectEquality(leaves, headWordNode);
if (StringUtils.isPunct(leaves.get(entity.getExtentTokenEnd()).label().value().trim())
&& (headWordIndex >= entity.getExtentTokenEnd()
|| headWordIndex < entity.getExtentTokenStart())) {
argRoot = tree.joinNode(leaves.get(entity.getExtentTokenStart()), leaves
.get(entity.getExtentTokenEnd() - 1));
headWordNode = argRoot.headTerminal(headFinder);
headWordIndex = getIndexByObjectEquality(leaves, headWordNode);
if (headWordIndex >= entity.getExtentTokenStart()
&& headWordIndex <= entity.getExtentTokenEnd() - 1) {
entity.setHeadTokenPosition(headWordIndex);
entity.setHeadTokenSpan(new Span(headWordIndex, headWordIndex + 1));
}
}
if (headWordIndex >= entity.getExtentTokenStart()
&& headWordIndex <= entity.getExtentTokenEnd()) {
entity.setHeadTokenPosition(headWordIndex);
entity.setHeadTokenSpan(new Span(headWordIndex, headWordIndex + 1));
} else {
// Re-parse the argument words by themselves
// Get the list of words in the arg by looking at the leaves between
// arg.getExtentTokenStart() and arg.getExtentTokenEnd() inclusive
List<String> argWords = new ArrayList<>();
for (int i = entity.getExtentTokenStart(); i <= entity.getExtentTokenEnd(); i++) {
argWords.add(leaves.get(i).label().value());
}
if (StringUtils.isPunct(argWords.get(argWords.size() - 1))) {
argWords.remove(argWords.size() - 1);
}
Tree argTree = parseStrings(argWords);
headWordNode = argTree.headTerminal(headFinder);
headWordIndex = getIndexByObjectEquality(argTree.getLeaves(),
headWordNode)
+ entity.getExtentTokenStart();
entity.setHeadTokenPosition(headWordIndex);
entity.setHeadTokenSpan(new Span(headWordIndex, headWordIndex + 1));
}
}
public static void main(String[] args) throws Exception {
// just a simple test, to make sure stuff works
Properties props = StringUtils.argsToProperties(args);
TestReader reader = new TestReader();
reader.setLoggerLevel(Level.INFO);
reader.setProcessor(new StanfordCoreNLP(props));
Annotation doc = reader.parse("/u/nlp/data/RothCONLL04/conll04.corp");
System.out.println(AnnotationUtils.datasetToString(doc));
}
}
只要记住在属性文件（roth.properties）中更改属性datasetReaderClass。
datasetReaderClass = test.TestReader