List of usage examples for edu.stanford.nlp.pipeline Annotation get
@Override @SuppressWarnings("unchecked") public <VALUE> VALUE get(Class<? extends Key<VALUE>> key)
From source file:StanfordCoreNLPXMLServer.java
License:Open Source License
public String parse(String s, String date) throws java.io.IOException { Annotation annotation = new Annotation(s); annotation.set(CoreAnnotations.DocDateAnnotation.class, date); pipeline.annotate(annotation);/*from w ww. j a va 2 s.co m*/ StringBuilder sb = new StringBuilder(); List<CoreMap> timexAnnsAll = annotation.get(TimeAnnotations.TimexAnnotations.class); sb.append(xmlPrefix); for (CoreMap cm : timexAnnsAll) { Timex t = cm.get(TimeAnnotations.TimexAnnotation.class); sb.append(t); sb.append("\n"); } sb.append(xmlPostfix); return sb.toString(); }
From source file:SentencePair.java
License:Open Source License
private void createSentence(String text, List<POSTaggedToken> sentence) { Annotation d = new Annotation(text); nlp.annotate(d);//from ww w.j a v a 2 s . c o m for (CoreMap ss : d.get(CoreAnnotations.SentencesAnnotation.class)) { for (CoreLabel token : ss.get(CoreAnnotations.TokensAnnotation.class)) { sentence.add(new POSTaggedToken(token.toString(), translateTag(token.tag()))); } } }
From source file:SentencePair.java
License:Open Source License
private void lemmatize(List<POSTaggedToken> sentence) { String text = ""; /* Convert the sentence back to a single string */ for (POSTaggedToken tt : sentence) { text += tt.token + " "; }/* w w w .j av a2s .c o m*/ Annotation d = new Annotation(text); nlp.annotate(d); for (CoreMap ss : d.get(CoreAnnotations.SentencesAnnotation.class)) { Iterator<CoreLabel> itToken = ss.get(CoreAnnotations.TokensAnnotation.class).iterator(); ListIterator<POSTaggedToken> itSentence = sentence.listIterator(); while (itToken.hasNext() && itSentence.hasNext()) { CoreLabel token = itToken.next(); POSTaggedToken tt = itSentence.next(); tt.lemma = token.lemma(); /* add a lemma to the POSTaggedToken */ itSentence.set(tt); } } }
From source file:Dependency.java
public static int findSentiment(String review) { int mainSentiment = 0; if (review != null && review.length() > 0) { int longest = 0; Annotation annotation = pipeline.process(review); for (CoreMap sentence : annotation.get(CoreAnnotations.SentencesAnnotation.class)) { Tree tree = sentence.get(SentimentCoreAnnotations.SentimentAnnotatedTree.class); int sentiment = RNNCoreAnnotations.getPredictedClass(tree); String partText = sentence.toString(); if (partText.length() > longest) { mainSentiment = sentiment; longest = partText.length(); }//w w w. jav a 2 s . c o m } } return mainSentiment; }
From source file:DateRecognitionFunction.java
License:Apache License
public static Set<String> ner(String text) { Annotation document = new Annotation(text); // run all Annotators on this text pipeline.annotate(document);/* w w w . j av a 2 s . c om*/ // 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(CoreAnnotations.SentencesAnnotation.class); Set<String> entities = new HashSet<>(); 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(CoreAnnotations.TokensAnnotation.class)) { // this is the text of the token String word = token.get(CoreAnnotations.TextAnnotation.class); // this is the NER label of the token String ne = token.get(CoreAnnotations.NamedEntityTagAnnotation.class); if (ne.equals("DATE")) { entities.add(word); } } } return entities; }
From source file:PersonRecognitionFunction.java
License:Apache License
public static Set<String> ner(String text) { Annotation document = new Annotation(text); // run all Annotators on this text pipeline.annotate(document);// ww w .j a va2s .com // 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(CoreAnnotations.SentencesAnnotation.class); Set<String> locations = new HashSet<>(); 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(CoreAnnotations.TokensAnnotation.class)) { // this is the text of the token String word = token.get(CoreAnnotations.TextAnnotation.class); // this is the NER label of the token String ne = token.get(CoreAnnotations.NamedEntityTagAnnotation.class); if (ne.equals("PERSON")) { locations.add(word); } } } return locations; }
From source file:Treeparse.java
public static void main(String[] args) { // TODO code application logic here Properties props = new Properties(); props.setProperty("annotators", "tokenize, ssplit, pos, lemma,parse"); StanfordCoreNLP pipeline = new StanfordCoreNLP(props); System.out.println("Enter the text:"); Scanner sc = new Scanner(System.in); text = sc.nextLine();// w ww .j a v a 2 s .c o m //while(text!="exit") //{ Annotation document = new Annotation(text); pipeline.annotate(document); List<CoreMap> sentences = document.get(SentencesAnnotation.class); for (CoreMap sentence : sentences) { token_length = sentence.get(TokensAnnotation.class).size(); arr1 = new String[POSTagger.token_length]; arr2 = new String[POSTagger.token_length]; int i = 0, j = 0; // System.out.println("Size"+token_length); for (CoreLabel token : sentence.get(TokensAnnotation.class)) { String word = token.get(TextAnnotation.class); String pos = token.get(PartOfSpeechAnnotation.class); // String ner = token.get(NamedEntityTagAnnotation.class); } Tree tree = sentence.get(TreeAnnotation.class); // System.out.println(tree); List<Tree> x = GetNounPhrases(tree); System.out.println(x); // Print words and Pos Tags /*for (Tree leaf : leaves) { Tree parent = leaf.parent(tree); System.out.print(leaf.label().value() + "-" + parent.label().value() + " "); }*/ } //System.out.println("Enter the text:"); //text=sc.nextLine(); }
From source file:SentimentAnalysisFunction.java
License:Apache License
public static int findSentiment(String tweet) { int mainSentiment = 0; if (tweet != null && tweet.length() > 0) { int longest = 0; Annotation annotation = pipeline.process(tweet); for (CoreMap sentence : annotation.get(CoreAnnotations.SentencesAnnotation.class)) { Tree tree = sentence.get(SentimentCoreAnnotations.SentimentAnnotatedTree.class); int sentiment = RNNCoreAnnotations.getPredictedClass(tree); String partText = sentence.toString(); if (partText.length() > longest) { mainSentiment = sentiment; longest = partText.length(); }//w w w . jav a 2s . c o m } } return mainSentiment; }
From source file:rev.java
/** * Processes requests for both HTTP <code>GET</code> and <code>POST</code> * methods.//ww w . ja va2 s . c o m * * @param request servlet request * @param response servlet response * @throws ServletException if a servlet-specific error occurs * @throws IOException if an I/O error occurs */ protected void processRequest(HttpServletRequest request, HttpServletResponse response) throws ServletException, IOException, SQLException, ClassNotFoundException { response.setContentType("text/html;charset=UTF-8"); try (PrintWriter out = response.getWriter()) { String a = request.getParameter("userMsg"); /* TODO output your page here. You may use following sample code. */ out.println("<!DOCTYPE HTML>\n" + "<head>\n" + "<link href=\"css/style.css\" rel=\"stylesheet\" type=\"text/css\" media=\"all\"/>\n" + "<link href=\"css/slider.css\" rel=\"stylesheet\" type=\"text/css\" media=\"all\"/>\n" + "<script type=\"text/javascript\" src=\"js/jquery-1.9.0.min.js\"></script>\n" + "<script type=\"text/javascript\" src=\"js/move-top.js\"></script>\n" + "<script type=\"text/javascript\" src=\"js/easing.js\"></script>\n" + "<script type=\"text/javascript\" src=\"js/jquery.nivo.slider.js\"></script>\n" + "<script type=\"text/javascript\">\n" + " $(window).load(function() {\n" + " $('#slider').nivoSlider();\n" + " });\n" + " <%! String n;\n" + " %>\n" + " <% \n" + " \n" + " n=(String)session.getAttribute(\"uname\"); \n" + " %>\n" + " </script>\n" + "</head>\n" + "<body>\n" + " <div class=\"header\">\n" + " <div class=\"headertop_desc\">\n" + " <div class=\"wrap\">\n" + " <div class=\"nav_list\">\n" + " \n" + " </div>\n" + " <div class=\"account_desc\">\n" + " <ul>\n" + " <li><a href=\"available.jsp\">Available movies</a></li>\n" + " <li><a href=\"takereview.jsp\">Review Movies</a></li>\n" + " <li><a href=\"rated.jsp\">Movies Rated</a></li>\n" + " <li><a href=\"abc.jsp\">Recommend Me</a></li>\n" + " \n" + " <li><a href=\"contact.html\">Contact</a></li>\n" + " <li><a href=\"logout\">Logout</a></li>\n" + " </ul>\n" + " </div>\n" + " <div class=\"clear\"></div>\n" + " </div>\n" + " </div>\n" + " <div class=\"wrap\">\n" + " <div class=\"header_top\">\n" + " <div class=\"logo\">\n" + " <a href=\"index.html\"><img src=\"images/logo1.jpg\" alt=\"\" /></a>\n" + " </div>\n" + " <div class=\"header_top_right\">\n" + " <div class=\"search_box\">\n" + " \n" + " </div>\n" + " <div class=\"clear\"></div>\n" + " </div>\n" + " \n" + " <div class=\"clear\"></div>\n" + " </div>\n" + " \n" + " \n" + "\n" + "\n" + ""); String line = "this book is too good to sleep"; Properties props = new Properties(); props.setProperty("annotators", "tokenize, ssplit, parse, sentiment, lemma"); StanfordCoreNLP pipeline = new StanfordCoreNLP(props); Annotation annotation = new Annotation(a); pipeline.annotate(annotation); annotation.toShorterString(); List<CoreMap> sentences = annotation.get(CoreAnnotations.SentencesAnnotation.class); if (sentences != null && !sentences.isEmpty()) { for (int i = 0; i < sentences.size(); i++) { CoreMap sentence = sentences.get(i); Tree tree = sentence.get(SentimentCoreAnnotations.SentimentAnnotatedTree.class); int sentiment = RNNCoreAnnotations.getPredictedClass(tree); String sentimentName = sentence.get(SentimentCoreAnnotations.SentimentClass.class); //Class.forName("com.mysql.jdbc.Driver"); /*String connectionURL = "jdbc:mysql://localhost:3306/review"; Connection conn; Statement stmt; ResultSet rs; conn = DriverManager.getConnection (connectionURL,"root",""); stmt = conn.createStatement(); // rs = stmt.executeQuery(""); out.println(); */ out.println("The sentence is:"); sentence.get(CoreAnnotations.TextAnnotation.class); //out.println("Sentiment of \n> \""++"\"\nis: " + sentiment+" (i.e., "+sentimentName+")"); out.println(sentimentName + " " + sentiment); if (sentimentName.equalsIgnoreCase("Negative")) { final String negative = "negative"; final String positive = "positive"; final String nuetral = "nuetral"; final String verypositive = "very positive"; final String verynegative = " very negative"; final DefaultCategoryDataset dataset = new DefaultCategoryDataset(); //out.println("NOT"); dataset.addValue(0, positive, positive); dataset.addValue(sentiment, negative, negative); dataset.addValue(0, nuetral, nuetral); dataset.addValue(0, verynegative, verynegative); dataset.addValue(0, verypositive, verypositive); JFreeChart barChart = ChartFactory.createBarChart("Movie Reviews", "Ratings", "Sentiments", dataset, PlotOrientation.VERTICAL, true, true, false); int width = 640; /* Width of the image */ int height = 480; /* Height of the image */ File BarChart = new File("/home/rishabh/NetBeansProjects/minor/web/images/k.jpeg"); ChartUtilities.saveChartAsJPEG(BarChart, barChart, width, height); out.println("<img src=\"images/BarChart.jpeg\">"); } else if (sentimentName.equalsIgnoreCase("Positive")) { final String negative = "negative"; final String positive = "positive"; final String nuetral = "nuetral"; final String verypositive = "very positive"; final String verynegative = " very negative"; final DefaultCategoryDataset dataset = new DefaultCategoryDataset(); // out.println("Good"); dataset.addValue(sentiment, positive, positive); dataset.addValue(0, negative, negative); dataset.addValue(0, nuetral, nuetral); dataset.addValue(0, verynegative, verynegative); dataset.addValue(0, verypositive, verypositive); JFreeChart barChart = ChartFactory.createBarChart("Movie Reviews", "Ratings", "Sentiments", dataset, PlotOrientation.VERTICAL, true, true, false); int width = 640; /* Width of the image */ int height = 480; /* Height of the image */ File BarChart = new File("/home/rishabh/NetBeansProjects/minor/web/images/k.jpeg"); ChartUtilities.saveChartAsJPEG(BarChart, barChart, width, height); out.println("<img src=\"images/BarChart1.jpeg\">"); } else if (sentimentName.equalsIgnoreCase("Neutral")) { final String negative = "negative"; final String positive = "positive"; final String nuetral = "nuetral"; final String verypositive = "very positive"; final String verynegative = " very negative"; final DefaultCategoryDataset dataset = new DefaultCategoryDataset(); //out.println("Good"); dataset.addValue(0, positive, positive); dataset.addValue(0, negative, negative); dataset.addValue(sentiment, nuetral, nuetral); dataset.addValue(0, verynegative, verynegative); dataset.addValue(0, verypositive, verypositive); JFreeChart barChart = ChartFactory.createBarChart("Movie Reviews", "Ratings", "Sentiments", dataset, PlotOrientation.VERTICAL, true, true, false); int width = 640; /* Width of the image */ int height = 480; /* Height of the image */ File BarChart = new File("/home/rishabh/NetBeansProjects/minor/web/images/k.jpeg"); ChartUtilities.saveChartAsJPEG(BarChart, barChart, width, height); out.println("<img src=\"images/BarChart2.jpeg\">"); } else if (sentimentName.equalsIgnoreCase("Very Positive")) { final String negative = "negative"; final String positive = "positive"; final String nuetral = "nuetral"; final String verypositive = "very positive"; final String verynegative = " very negative"; final DefaultCategoryDataset dataset = new DefaultCategoryDataset(); //out.println("Good"); dataset.addValue(0, positive, positive); dataset.addValue(0, negative, negative); dataset.addValue(0, nuetral, nuetral); dataset.addValue(0, verynegative, verynegative); dataset.addValue(sentiment, verypositive, verypositive); JFreeChart barChart = ChartFactory.createBarChart("Movie Reviews", "Ratings", "Sentiments", dataset, PlotOrientation.VERTICAL, true, true, false); int width = 640; /* Width of the image */ int height = 480; /* Height of the image */ File BarChart = new File("/home/rishabh/NetBeansProjects/minor/web/images/k.jpeg"); ChartUtilities.saveChartAsJPEG(BarChart, barChart, width, height); out.println("<img src=\"images/BarChart4.jpeg\">"); } else if (sentimentName.equalsIgnoreCase("Very Negative")) { final String negative = "negative"; final String positive = "positive"; final String nuetral = "nuetral"; final String verypositive = "very positive"; final String verynegative = " very negative"; final DefaultCategoryDataset dataset = new DefaultCategoryDataset(); //out.println("Good"); dataset.addValue(0, positive, positive); dataset.addValue(0, negative, negative); dataset.addValue(0, nuetral, nuetral); dataset.addValue(sentiment, verynegative, verynegative); dataset.addValue(0, verypositive, verypositive); JFreeChart barChart = ChartFactory.createBarChart("Movie Reviews", "Ratings", "Sentiments", dataset, PlotOrientation.VERTICAL, true, true, false); int width = 640; /* Width of the image */ int height = 480; /* Height of the image */ File BarChart = new File("/home/rishabh/NetBeansProjects/minor/web/images/k.jpeg"); ChartUtilities.saveChartAsJPEG(BarChart, barChart, width, height); out.println("<img src=\"images/BarChart3.jpeg\">"); } } } out.println("<div class=\"footer\">\n" + " <div class=\"wrap\">\n" + " <div class=\"section group\">\n" + " <div class=\"col span\">\n" + " <h4>Information</h4>\n" + " <ul>\n" + " <li><a href=\"#\">About Us</a></li>\n" + " \n" + " <li><a href=\"contact.html\">Contact Us</a></li>\n" + " </ul>\n" + " </div>\n" + " <div class=\"col span\">\n" + " <h4>Know us better</h4>\n" + " <ul>\n" + " <li><a href=\"#\">About Us</a></li>\n" + " \n" + " <li><a href=\"contact.html\">Site Map</a></li>\n" + " <li><a href=\"#\">Search Terms</a></li>\n" + " </ul>\n" + " </div>\n" + " \n" + " <div class=\"col span\">\n" + " <h4>Contact</h4>\n" + " <ul>\n" + " <li><span>9971825755</span></li>\n" + " <li><span>8130527232</span></li>\n" + " </ul>\n" + " <div class=\"social-icons\">\n" + " <h4>Follow Us</h4>\n" + " <ul>\n" + " <li><a href=\"#\" target=\"_blank\"><img src=\"images/facebook.png\" alt=\"\" /></a></li>\n" + " <li><a href=\"#\" target=\"_blank\"><img src=\"images/twitter.png\" alt=\"\" /></a></li>\n" + " <li><a href=\"#\" target=\"_blank\"><img src=\"images/skype.png\" alt=\"\" /> </a></li>\n" + " <li><a href=\"#\" target=\"_blank\"> <img src=\"images/linkedin.png\" alt=\"\" /></a></li>\n" + " <div class=\"clear\"></div>\n" + " </ul>\n" + " </div>\n" + " </div>\n" + " </div>\n" + " <div class=\"copy_right\">\n" + " <p>Company Name All rights Reseverd </p>\n" + " </div>\n" + " </div>\n" + " </div>\n" + " <script type=\"text/javascript\">\n" + " $(document).ready(function() {\n" + " $().UItoTop({ easingType: 'easeOutQuart' });\n" + "\n" + " });\n" + " </script>\n" + " <a href=\"#\" id=\"toTop\"><span id=\"toTopHover\"> </span></a>\n" + "</body>\n" + "</html>\n" + "\n" + ""); } }
From source file:unCompressedIndex.java
public static String lemmatize(String documentText) { List<String> lemmas = new LinkedList<String>(); // Create an empty Annotation just with the given text Annotation document = new Annotation(documentText); // run all Annotators on this text pipeline.annotate(document);/*from ww w .j a va2 s . c o m*/ // Iterate over all of the sentences found String temp = ""; List<CoreMap> sentences = document.get(SentencesAnnotation.class); for (CoreMap sentence : sentences) { // Iterate over all tokens in a sentence for (CoreLabel token : sentence.get(TokensAnnotation.class)) { temp = token.get(LemmaAnnotation.class); lemmas.add(temp); } } return lemmas.get(0).toString(); //System.out.println("lemmas:"+lemmas.get(0)); }