Examples with StanfordCoreNLP edu.stanford.nlp.pipeline.StanfordCoreNLP used on opensource projects

Example 26 with StanfordCoreNLP

use of edu.stanford.nlp.pipeline.StanfordCoreNLP in project CoreNLP by stanfordnlp.

the class MachineReading method makeMachineReading.

public static MachineReading makeMachineReading(String[] args) throws IOException {
    // install global parameters
    MachineReading mr = new MachineReading(args);
    //TODO:
    ArgumentParser.fillOptions(MachineReadingProperties.class, args);
    //Arguments.parse(args, mr);
    log.info("PERCENTAGE OF TRAIN: " + MachineReadingProperties.percentageOfTrain);
    // convert args to properties
    Properties props = StringUtils.argsToProperties(args);
    if (props == null) {
        throw new RuntimeException("ERROR: failed to find Properties in the given arguments!");
    }
    String logLevel = props.getProperty("logLevel", "INFO");
    setLoggerLevel(Level.parse(logLevel.toUpperCase()));
    // install reader specific parameters
    GenericDataSetReader reader = mr.makeReader(props);
    GenericDataSetReader auxReader = mr.makeAuxReader();
    Level readerLogLevel = Level.parse(MachineReadingProperties.readerLogLevel.toUpperCase());
    reader.setLoggerLevel(readerLogLevel);
    if (auxReader != null) {
        auxReader.setLoggerLevel(readerLogLevel);
    }
    log.info("The reader log level is set to " + readerLogLevel);
    //Execution.fillOptions(GenericDataSetReaderProps.class, args);
    //Arguments.parse(args, reader);
    // create the pre-processing pipeline
    StanfordCoreNLP pipe = new StanfordCoreNLP(props, false);
    reader.setProcessor(pipe);
    if (auxReader != null) {
        auxReader.setProcessor(pipe);
    }
    // create the results printers
    mr.makeResultsPrinters(args);
    return mr;
}

Example 27 with StanfordCoreNLP

use of edu.stanford.nlp.pipeline.StanfordCoreNLP in project CoreNLP by stanfordnlp.

the class AceReader method main.

// simple testing code
public static void main(String[] args) throws IOException {
    Properties props = StringUtils.argsToProperties(args);
    AceReader r = new AceReader(new StanfordCoreNLP(props, false), false);
    r.setLoggerLevel(Level.INFO);
    r.parse("/scr/nlp/data/ACE2005/");
    // Annotation a = r.parse("/user/mengqiu/scr/twitter/nlp/corpus_prep/standalone/ar/data");
    // BasicEntityExtractor.saveCoNLLFiles("/tmp/conll", a, false, false);
    log.info("done");
}

Example 28 with StanfordCoreNLP

use of edu.stanford.nlp.pipeline.StanfordCoreNLP in project CoreNLP by stanfordnlp.

the class OpenIEDemo method main.

public static void main(String[] args) throws Exception {
    // Create the Stanford CoreNLP pipeline
    Properties props = PropertiesUtils.asProperties("annotators", "tokenize,ssplit,pos,lemma,depparse,natlog,openie");
    StanfordCoreNLP pipeline = new StanfordCoreNLP(props);
    // Annotate an example document.
    String text;
    if (args.length > 0) {
        text = IOUtils.slurpFile(args[0]);
    } else {
        text = "Obama was born in Hawaii. He is our president.";
    }
    Annotation doc = new Annotation(text);
    pipeline.annotate(doc);
    // Loop over sentences in the document
    int sentNo = 0;
    for (CoreMap sentence : doc.get(CoreAnnotations.SentencesAnnotation.class)) {
        System.out.println("Sentence #" + ++sentNo + ": " + sentence.get(CoreAnnotations.TextAnnotation.class));
        // Print SemanticGraph
        System.out.println(sentence.get(SemanticGraphCoreAnnotations.EnhancedDependenciesAnnotation.class).toString(SemanticGraph.OutputFormat.LIST));
        // Get the OpenIE triples for the sentence
        Collection<RelationTriple> triples = sentence.get(NaturalLogicAnnotations.RelationTriplesAnnotation.class);
        // Print the triples
        for (RelationTriple triple : triples) {
            System.out.println(triple.confidence + "\t" + triple.subjectLemmaGloss() + "\t" + triple.relationLemmaGloss() + "\t" + triple.objectLemmaGloss());
        }
        // Alternately, to only run e.g., the clause splitter:
        List<SentenceFragment> clauses = new OpenIE(props).clausesInSentence(sentence);
        for (SentenceFragment clause : clauses) {
            System.out.println(clause.parseTree.toString(SemanticGraph.OutputFormat.LIST));
        }
        System.out.println();
    }
}

Example 29 with StanfordCoreNLP

use of edu.stanford.nlp.pipeline.StanfordCoreNLP in project CoreNLP by stanfordnlp.

the class TokensRegexDemo method main.

public static void main(String[] args) throws IOException {
    String rules;
    if (args.length > 0) {
        rules = args[0];
    } else {
        rules = "edu/stanford/nlp/ling/tokensregex/demo/rules/expr.rules.txt";
    }
    PrintWriter out;
    if (args.length > 2) {
        out = new PrintWriter(args[2]);
    } else {
        out = new PrintWriter(System.out);
    }
    CoreMapExpressionExtractor<MatchedExpression> extractor = CoreMapExpressionExtractor.createExtractorFromFiles(TokenSequencePattern.getNewEnv(), rules);
    StanfordCoreNLP pipeline = new StanfordCoreNLP(PropertiesUtils.asProperties("annotators", "tokenize,ssplit,pos,lemma,ner"));
    Annotation annotation;
    if (args.length > 1) {
        annotation = new Annotation(IOUtils.slurpFileNoExceptions(args[1]));
    } else {
        annotation = new Annotation("( ( five plus three plus four ) * 2 ) divided by three");
    }
    pipeline.annotate(annotation);
    // An Annotation is a Map and you can get and use the various analyses individually.
    out.println();
    // The toString() method on an Annotation just prints the text of the Annotation
    // But you can see what is in it with other methods like toShorterString()
    out.println("The top level annotation");
    out.println(annotation.toShorterString());
    List<CoreMap> sentences = annotation.get(CoreAnnotations.SentencesAnnotation.class);
    for (CoreMap sentence : sentences) {
        List<MatchedExpression> matchedExpressions = extractor.extractExpressions(sentence);
        for (MatchedExpression matched : matchedExpressions) {
            // Print out matched text and value
            out.println("Matched expression: " + matched.getText() + " with value " + matched.getValue());
            // Print out token information
            CoreMap cm = matched.getAnnotation();
            for (CoreLabel token : cm.get(CoreAnnotations.TokensAnnotation.class)) {
                String word = token.get(CoreAnnotations.TextAnnotation.class);
                String lemma = token.get(CoreAnnotations.LemmaAnnotation.class);
                String pos = token.get(CoreAnnotations.PartOfSpeechAnnotation.class);
                String ne = token.get(CoreAnnotations.NamedEntityTagAnnotation.class);
                out.println("  Matched token: " + "word=" + word + ", lemma=" + lemma + ", pos=" + pos + ", ne=" + ne);
            }
        }
    }
    out.flush();
}

Example 30 with StanfordCoreNLP

use of edu.stanford.nlp.pipeline.StanfordCoreNLP in project CoreNLP by stanfordnlp.

the class TokensRegexRetokenizeDemo method main.

public static void main(String[] args) throws IOException {
    PrintWriter out;
    String rules;
    if (args.length > 0) {
        rules = args[0];
    } else {
        rules = "edu/stanford/nlp/ling/tokensregex/demo/rules/retokenize.rules.txt";
    }
    if (args.length > 2) {
        out = new PrintWriter(args[2]);
    } else {
        out = new PrintWriter(System.out);
    }
    String text;
    if (args.length > 1) {
        text = IOUtils.slurpFileNoExceptions(args[1]);
    } else {
        text = "Do we tokenize on hyphens? one-two-three-four.  How about dates? 03-16-2015.";
    }
    Properties propertiesDefaultTokenize = new Properties();
    propertiesDefaultTokenize.setProperty("annotators", "tokenize,ssplit,pos,lemma,ner");
    StanfordCoreNLP pipelineDefaultRetokenize = new StanfordCoreNLP();
    out.println("Default tokenization: ");
    runPipeline(pipelineDefaultRetokenize, text, out);
    Properties properties = new Properties();
    properties.setProperty("annotators", "tokenize,retokenize,ssplit,pos,lemma,ner");
    properties.setProperty("customAnnotatorClass.retokenize", "edu.stanford.nlp.pipeline.TokensRegexAnnotator");
    properties.setProperty("retokenize.rules", rules);
    StanfordCoreNLP pipelineWithRetokenize = new StanfordCoreNLP(properties);
    out.println();
    out.println("Always tokenize hyphens: ");
    runPipeline(pipelineWithRetokenize, text, out);
}