斯坦福 CoreNLP
Stanford CoreNLP 是一种流行的自然语言处理工具包,支持许多核心 NLP 任务。
要下载并安装该程序,请下载发行包并在类路径中包含必要的*.jar
文件,或者从 Maven 中心添加依赖项。有关详细信息,请参阅下载页面 。例如:
curl http://nlp.stanford.edu/software/stanford-corenlp-full-2015-12-09.zip -o corenlp.zip
unzip corenlp.zip
cd corenlp
export CLASSPATH="$CLASSPATH:`pwd`/*
运行 CoreNLP 工具有三种支持的方法:(1)使用基本完全可自定义的 API ,(2)使用 Simple CoreNLP API,或(3)使用 CoreNLP 服务器 。下面给出每个的简单使用示例。作为一个激励用例,这些例子将用于预测句子的句法分析。
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CoreNLP API
public class CoreNLPDemo { public static void main(String[] args) { // 1. Set up a CoreNLP pipeline. This should be done once per type of annotation, // as it's fairly slow to initialize. // creates a StanfordCoreNLP object, with POS tagging, lemmatization, NER, parsing, and coreference resolution Properties props = new Properties(); props.setProperty("annotators", "tokenize, ssplit, parse"); StanfordCoreNLP pipeline = new StanfordCoreNLP(props); // 2. Run the pipeline on some text. // read some text in the text variable String text = "the quick brown fox jumped over the lazy dog"; // Add your text here! // create an empty Annotation just with the given text Annotation document = new Annotation(text); // run all Annotators on this text pipeline.annotate(document); // 3. Read off the result // Get the list of sentences in the document List<CoreMap> sentences = document.get(CoreAnnotations.SentencesAnnotation.class); for (CoreMap sentence : sentences) { // Get the parse tree for each sentence Tree parseTree = sentence.get(TreeAnnotations.TreeAnnotation.class); // Do something interesting with the parse tree! System.out.println(parseTree); } } }
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简单的 CoreNLP
public class CoreNLPDemo { public static void main(String[] args) { String text = "The quick brown fox jumped over the lazy dog"); // your text here! Document document = new Document(text); // implicitly runs tokenizer for (Sentence sentence : document.sentences()) { Tree parseTree = sentence.parse(); // implicitly runs parser // Do something with your parse tree! System.out.println(parseTree); } } }
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CoreNLP 服务器
使用以下命令启动服务器(适当地设置类路径):
java -mx4g -cp "*" edu.stanford.nlp.pipeline.StanfordCoreNLPServer [port] [timeout]
获取给定注释器集的 JSON 格式输出,并将其打印到标准输出:
wget --post-data 'The quick brown fox jumped over the lazy dog.' 'localhost:9000/?properties={"annotators":"tokenize,ssplit,parse","outputFormat":"json"}' -O -
要从 JSON 获取我们的解析树,我们可以将 JSON 导航到
sentences[i].parse
。