Question

我是这个领域的新手。我有这种形式的依赖关系：

amod(clarity-2, sound-1)
nsubj(good-6, clarity-2)
cop(good-6, is-3)
advmod(good-6, also-4)
neg(good-6, not-5)
root(ROOT-0, good-6)
nsubj(ok-10, camera-8)
cop(ok-10, is-9)
ccomp(good-6, ok-10)

如链接中所述，我们必须将此依赖关系转换为点格式，然后使用Graphviz绘制“依赖关系树”。我无法理解如何将此依赖关系传递给edu.stanford.nlp.semgraph.SemanticGraph的toDotFormat（）函数。当我给这个字符串时，'amod（clarity-2，sound-1）'作为toDotFormat（）的输入，我以这种形式获得输出digraph amod（clarity-2，sound-1）{}。我正在尝试这里给出的解决方案how to get a dependency tree with Stanford NLP parser

Answer 1

您需要在整个依赖关系树上调用toDotFormat。你是如何在一开始就生成这些依赖树的？

如果您正在使用StanfordCoreNLP渠道，则可以轻松添加toDotFormat电话：

Properties properties = new Properties();
props.put("annotators", "tokenize, ssplit, pos, depparse");
StanfordCoreNLP pipeline = new StanfordCoreNLP(props);

String text = "This is a sentence I want to parse.";
Annotation document = new Annotation(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) {
  // this is the Stanford dependency graph of the current sentence
  SemanticGraph dependencies = sentence.get(CollapsedCCProcessedDependenciesAnnotation.class);
  System.out.println(dependencies.toDotFormat());
}

将斯坦福依赖关系转换为点格式

1 个答案: