Package org.apache.clerezza.rdf.core

Examples of org.apache.clerezza.rdf.core.Language

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    LiteralFactory lf = LiteralFactory.getInstance();

    //we need also to create a fise:TextAnnotation to test disambiguation
    String selected = "Angela Merkel";
    Language en = new Language("en");
    UriRef textAnnotation = EnhancementEngineHelper.createTextEnhancement(ci,
        new DBPSpotlightSpotEnhancementEngine());
    MGraph model = ci.getMetadata();
    model.add(new TripleImpl(textAnnotation, Properties.ENHANCER_SELECTED_TEXT,
        new PlainLiteralImpl(selected,en)));
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                    .getDataType().getUnicodeString()));
        } else if (resource instanceof PlainLiteral) {
            value = doc.createElement("literal");
            value.appendChild(doc.createTextNode(((PlainLiteral) resource)
                    .getLexicalForm()));
            Language lang = ((PlainLiteral) resource).getLanguage();
            if (lang != null) {
                value.setAttribute("xml:lang", (lang.toString()));
            }
        } else {
            value = doc.createElement("bnode");
            value.appendChild(doc.createTextNode(((BNode) resource).toString()));
        }
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    }
        String language = EnhancementEngineHelper.getLanguage(ci);
        if (language == null) {
            throw new IllegalStateException("Unable to extract Language for " + "ContentItem " + ci.getUri() + ": This is also checked in the canEnhance " + "method! -> This indicated an Bug in the implementation of the " + "EnhancementJobManager!");
        }
        Language lang = new Language(language); //used for the palin literals in TextAnnotations
    try {
      List<NamedEntity> lista = this.client.extractEntities(text, language);
      LiteralFactory literalFactory = LiteralFactory.getInstance();

      MGraph g = ci.getMetadata();
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    @Override
    public void computeEnhancements(ContentItem ci) throws EngineException {
        AnalysedText at = getAnalysedText(this, ci, true);
        String lang = EnhancementEngineHelper.getLanguage(ci);
        Language language = lang == null ? null : new Language(lang);
        //now iterate over the AnalysedText data and create the RDF representation
        //TODO: make configureable
        boolean sentences = true;
        boolean phrases = true;
        boolean words = true;
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    public final void addPlainLiteral(String subj, String pred, String content, String lang) {
        Literal lit;
        if (lang == null || lang.equals("")) {
            lit = new PlainLiteralImpl(content);
        } else {
            lit = new PlainLiteralImpl(content, new Language(lang));
        }
        addTriple(convertNonLiteral(subj), new UriRef(pred), lit);
    }
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            String graph) {
        final NonLiteral subject = getNonLiteral(s);
        final UriRef predicate = new UriRef(p);
        Resource object;
        if (language != null) {
            object = new PlainLiteralImpl(value, new Language(language));
        } else {
            if (datatype != null) {
                object = new TypedLiteralImpl(value, new UriRef(datatype));
            } else {
                object = new PlainLiteralImpl(value);
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Related Classes of org.apache.clerezza.rdf.core.Language

  • com.github.jsonldjava.clerezza.ClerezzaTripleCallback
  • org.apache.clerezza.jaxrs.sparql.providers.ResultSetJsonMessageBodyWriter
  • org.apache.clerezza.jaxrs.sparql.providers.ResultSetXmlMessageBodyWriter
  • org.apache.clerezza.platform.concepts.core.ConceptManipulator
  • org.apache.clerezza.platform.language.LanguageDescription
  • org.apache.clerezza.rdf.core.impl.PlainLiteralImplTest
  • org.apache.clerezza.rdf.core.sparql.QueryParserTest
  • org.apache.clerezza.rdf.core.test.MGraphTest
  • org.apache.clerezza.rdf.jena.commons.Jena2TriaUtil
  • org.apache.clerezza.rdf.rdfjson.parser.RdfJsonParsingProvider
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