private List<Pair<List<Integer>, String>> predictFrames(
Sentence sentence, List<List<Integer>> targets) {
final List<Pair<List<Integer>, String>> idResult = Lists.newArrayList();
for (List<Integer> targetTokenIdxs : targets) {
final String frame = idModel.getBestFrame(targetTokenIdxs, sentence);
idResult.add(Pair.of(targetTokenIdxs, frame));
}
return idResult;
}
public static Semafor getSemaforInstance(String modelDirectory)
throws IOException, ClassNotFoundException, URISyntaxException {
final String requiredDataFilename =
new File(modelDirectory, REQUIRED_DATA_FILENAME).getAbsolutePath();
final String alphabetFilename = new File(modelDirectory, ALPHABET_FILENAME).getAbsolutePath();
final String frameElementMapFilename =
new File(modelDirectory, FRAME_ELEMENT_MAP_FILENAME).getAbsolutePath();
final String argModelFilename = new File(modelDirectory, ARG_MODEL_FILENAME).getAbsolutePath();
// unpack required data
final RequiredDataForFrameIdentification r = readObject(requiredDataFilename);
final Set<String> allRelatedWords = r.getAllRelatedWords();
final GraphBasedFrameIdentifier idModel = GraphBasedFrameIdentifier.getInstance(modelDirectory);
final RoteSegmenter segmenter = new RoteSegmenter(allRelatedWords);
System.err.println("Initializing alphabet for argument identification..");
final Map<String, Integer> argIdFeatureIndex =
DataPrep.readFeatureIndex(new File(alphabetFilename));
final FEDict frameElementsForFrame = FEDict.fromFile(frameElementMapFilename);
final Decoding decoder = Decoding.fromFile(argModelFilename, alphabetFilename);
return new Semafor(
allRelatedWords, frameElementsForFrame, segmenter, idModel, decoder, argIdFeatureIndex);
}
