private POSTagger getPOSTagger(String language) { String modelName = languageConfig.getParameter(language,MODEL_NAME_PARAM); try { POSModel model; if(modelName == null){ //use the default model = openNLP.getPartOfSpeechModel(language); } else { model = openNLP.getModel(POSModel.class, modelName, null); } if(model != null) { log.debug("POS Tagger Model {} for lanugage '{}' version: {}", new Object[]{model.getClass().getSimpleName(), model.getLanguage(), model.getVersion() != null ? model.getVersion() : "undefined"}); return new POSTaggerME(model); } } catch (Exception e) { log.warn("Unable to load POS model for language '"+language+"'!",e); } log.debug("POS tagging Model for Language '{}' not available.", language); return null; }
private ChunkerME initChunker(String language) { isLangaugeConfigured(this,languageConfiguration,language, true); //check if the parsed language is ok String modelName = languageConfiguration.getParameter(language, MODEL_PARAM_NAME); ChunkerModel model; try { if(modelName == null){ // the default model model = openNLP.getChunkerModel(language); } else { model = openNLP.getModel(ChunkerModel.class, modelName, null); } }catch (IOException e) { log.warn("Unable to load Chunker model for language '"+language + "' (model: "+(modelName == null ? "default" : modelName)+")", e); return null; } catch (RuntimeException e){ log.warn("Error while creating ChunkerModel for language '"+language + "' (model: "+(modelName == null ? "default" : modelName)+")", e); return null; } if(model == null){ log.trace("no Chunker Model for language {}",language); return null; } else { return new ChunkerME(model); } }
String modelName = languageConfig.getParameter(language, MODEL_NAME_PARAM); if(modelName == null){ try {
String modelName = languageConfig.getParameter(language, MODEL_NAME_PARAM); if(modelName == null){ return openNLP.getTokenizer(language);
@Override public String[] tokenize(String label, String language) { if(label == null){ throw new IllegalArgumentException("The parsed Label MUST NOT be NULL!"); } if(languageConfig.isLanguage(language)){ String modelName = languageConfig.getParameter(language, PARAM_MODEL); if(modelName != null){ try { TokenizerModel model = openNlp.getModel(TokenizerModel.class, modelName, null); return new TokenizerME(model).tokenize(label); } catch (Exception e) { log.warn("Unable to load configured TokenizerModel '"+modelName + "' for language '"+language + "! Fallback to default Tokenizers",e); } } //fallback to the defaults return openNlp.getTokenizer(language).tokenize(label); } else { //language not configured return null; } }