public void Analysis(string path)
{
var document = this.ReadAnnotation(path);
Properties props = new Properties();
//props.setProperty("annotators", "tokenize,ssplit,pos,lemma,ner,parse,relation,,mention,coref");
//var modelsDirectory = jarRoot ;
// Loading POS Tagger
//String modPath = @"D:\Tesis2016\Jarvis\Lincoln\Models\";
//props.put("pos.model", modPath + @"pos-tagger\english-bidirectional-distsim.tagger");
//props.put("ner.model", modPath + "ner/english.all.3class.distsim.crf.ser.gz");
//props.put("parse.model", modPath + "lexparser/englishPCFG.ser.gz");
//props.put("annotators", "tokenize, ssplit, pos, lemma, ner, parse, dcoref");
//props.put("sutime.binders", "0");
//props.put("sutime.rules", modPath + "sutime/defs.sutime.txt, " + modPath + "sutime/english.sutime.txt");
//props.put("dcoref.demonym", modPath + "dcoref/demonyms.txt");
//props.put("dcoref.states", modPath + "dcoref/state-abbreviations.txt");
//props.put("dcoref.animate", modPath + "dcoref/animate.unigrams.txt");
//props.put("dcoref.inanimate", modPath + "dcoref/inanimate.unigrams.txt");
//props.put("dcoref.big.gender.number", modPath + "dcoref/gender.data.gz");
//props.put("dcoref.countries", modPath + "dcoref/countries");
//props.put("dcoref.states.provinces", modPath + "dcoref/statesandprovinces");
//props.put("dcoref.singleton.model", modPath + "dcoref/singleton.predictor.ser");
//props.put("ner.useSUTime", "0");
props.setProperty("annotators", "tokenize, ssplit, pos, lemma, ner, parse, dcoref");
props.setProperty("annotators", "tokenize, ssplit, pos, lemma, ner, parse, dcoref");
props.setProperty("sutime.binders", "0");
props.setProperty("ner.useSUTime", "false");
var jarRoot = @"D:\Tesis2016\Jarvis\Lincoln\Models";
var curDir = Environment.CurrentDirectory;
System.IO.Directory.SetCurrentDirectory(jarRoot);
var pipeline = new StanfordCoreNLP(props);
pipeline.annotate(document);
System.IO.Directory.SetCurrentDirectory(curDir);
FileOutputStream os = new FileOutputStream(new File("coreference_output.xml"));
pipeline.xmlPrint(document, os);
}
//使用nlp將文章分析後回傳key
private List<string> nlp(string sentence)
{
List<string> return_key = new List<string>();
string Relay_file = ".\\xml";
string Relay_name = "Relay.xml";
string Relay_path = Relay_file+ "\\" + Relay_name;
// Path to the folder with models extracted from `stanford-corenlp-3.4-models.jar`
var jarRoot = @"stanford-corenlp-3.5.2-models\";
// Annotation pipeline configuration
var props = new java.util.Properties();
props.setProperty("ner.useSUTime", "false");
props.setProperty("annotators", "tokenize, ssplit, pos, lemma, ner, parse, dcoref");
props.setProperty("sutime.binders", "0");
// We should change current directory, so StanfordCoreNLP could find all the model files automatically
var curDir = Environment.CurrentDirectory;
System.IO.Directory.SetCurrentDirectory(jarRoot);
var pipeline = new StanfordCoreNLP(props);
System.IO.Directory.SetCurrentDirectory(curDir);
// Annotation
var annotation = new Annotation(sentence);
pipeline.annotate(annotation);
//輸出nlp分析結果至Relay.xml
FileOutputStream os = new FileOutputStream(new File(Relay_file, Relay_name));
pipeline.xmlPrint(annotation, os);
os.close();
//呼叫ner將單字組合為有意義的key組裝
foreach(string k in ner(Relay_path))
{
return_key.Add(k);
}
return return_key;
}
