Question

public static void main(String[] args) {
   Properties props = new Properties();
props.put("annotators", "tokenize, ssplit, pos, lemma, ner, parse, dcoref");
StanfordCoreNLP pipeline = new StanfordCoreNLP(props);

// read some text in the text variable
String text = "the quick fox jumps over the lazy dog";

// create an empty Annotation just with the given text
Annotation document = new Annotation(text);

// run all Annotators on this text
pipeline.annotate(document);

// these are all the sentences in this document
// a CoreMap is essentially a Map that uses class objects as keys and has values with custom types
List<CoreMap> sentences = document.get(SentencesAnnotation.class);

for(CoreMap sentence: sentences) {
  // traversing the words in the current sentence
  // a CoreLabel is a CoreMap with additional token-specific methods
  for (CoreLabel token: sentence.get(TokensAnnotation.class)) {
    // this is the text of the token
    String word = token.get(TextAnnotation.class);
    // this is the POS tag of the token
    String pos = token.get(PartOfSpeechAnnotation.class);
    // this is the NER label of the token
    String ne = token.get(NamedEntityTagAnnotation.class);       
  }

  // this is the parse tree of the current sentence
  Tree tree = sentence.get(TreeAnnotation.class);

  // this is the Stanford dependency graph of the current sentence
  SemanticGraph dependencies = sentence.get(CollapsedCCProcessedDependenciesAnnotation.class);
}

// This is the coreference link graph
// Each chain stores a set of mentions that link to each other,
// along with a method for getting the most representative mention
// Both sentence and token offsets start at 1!
Map<Integer, CorefChain> graph = 
  document.get(CorefChainAnnotation.class);
}

}

我想运行我的程序但我收到此错误

Loading classifier from edu/stanford/nlp/models/ner/english.all.3class.distsim.crf.ser.gz ... Exception in thread "main" java.lang.OutOfMemoryError: Java heap space
at java.lang.StringBuilder.toString(StringBuilder.java:405)
at java.io.ObjectInputStream$BlockDataInputStream.readUTFBody(ObjectInputStream.java:3066)
at java.io.ObjectInputStream$BlockDataInputStream.readUTF(ObjectInputStream.java:2862)
at java.io.ObjectInputStream.readString(ObjectInputStream.java:1636)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1339)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:370)
at java.util.HashMap.readObject(HashMap.java:1154)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:601)
at java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1004)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1891)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1796)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1348)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1989)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1913)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1796)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1348)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:370)
at edu.stanford.nlp.ie.crf.CRFClassifier.loadClassifier(CRFClassifier.java:2255)
at edu.stanford.nlp.ie.AbstractSequenceClassifier.loadClassifier(AbstractSequenceClassifier.java:1444)
at edu.stanford.nlp.ie.AbstractSequenceClassifier.loadClassifier(AbstractSequenceClassifier.java:1421)
at edu.stanford.nlp.ie.AbstractSequenceClassifier.loadClassifier(AbstractSequenceClassifier.java:1500)
at edu.stanford.nlp.ie.AbstractSequenceClassifier.loadClassifier(AbstractSequenceClassifier.java:1487)
at edu.stanford.nlp.ie.crf.CRFClassifier.getClassifier(CRFClassifier.java:2386)
at edu.stanford.nlp.ie.ClassifierCombiner.loadClassifierFromPath(ClassifierCombiner.java:130)
at edu.stanford.nlp.ie.ClassifierCombiner.loadClassifiers(ClassifierCombiner.java:116)
at edu.stanford.nlp.ie.ClassifierCombiner.<init>(ClassifierCombiner.java:98)
at edu.stanford.nlp.ie.NERClassifierCombiner.<init>(NERClassifierCombiner.java:64)
at edu.stanford.nlp.pipeline.StanfordCoreNLP$6.create(StanfordCoreNLP.java:500)
at edu.stanford.nlp.pipeline.StanfordCoreNLP$6.create(StanfordCoreNLP.java:471)

我不知道如何增加堆大小或此错误与我无法理解的另一个问题有关。任何人都可以帮助我？（对不起，我的英语不好）

Answer 1

如果您的项目是java项目---＆gt;右键单击项目---＆gt;选择属性---＆gt;单击右侧的Run ---＆gt;您将看到VM Options，您需要输入堆设置。

示例：

-Xmx512m

注意：如果512不起作用，请将其增加到1024并尝试。

使用java创建对象CoreNLP

1 个答案: