public void TestOutcomesForSingleSentence() {
const string sentence = "That_DT sounds_VBZ good_JJ ._.";
var sample = POSSample.Parse(sentence);
var eventStream = new POSSampleEventStream(new GenericObjectStream<POSSample>(sample));
Assert.AreEqual("DT", eventStream.Read().Outcome);
Assert.AreEqual("VBZ", eventStream.Read().Outcome);
Assert.AreEqual("JJ", eventStream.Read().Outcome);
Assert.AreEqual(".", eventStream.Read().Outcome);
Assert.Null(eventStream.Read());
}
public void TestOutcomesForSingleSentence()
{
const string sentence = "That_DT sounds_VBZ good_JJ ._.";
var sample = POSSample.Parse(sentence);
var eventStream = new POSSampleEventStream(new GenericObjectStream <POSSample>(sample));
Assert.AreEqual("DT", eventStream.Read().Outcome);
Assert.AreEqual("VBZ", eventStream.Read().Outcome);
Assert.AreEqual("JJ", eventStream.Read().Outcome);
Assert.AreEqual(".", eventStream.Read().Outcome);
Assert.Null(eventStream.Read());
}
/// <summary>
/// Trains a Part of Speech model with the given parameters.
/// </summary>
/// <param name="languageCode">The language code.</param>
/// <param name="samples">The data samples.</param>
/// <param name="parameters">The machine learnable parameters.</param>
/// <param name="factory">The sentence detector factory.</param>
/// <param name="monitor">
/// A evaluation monitor that can be used to listen the messages during the training or it can cancel the training operation.
/// This argument can be a <c>null</c> value.
/// </param>
/// <returns>The trained <see cref="POSModel"/> object.</returns>
/// <exception cref="System.NotSupportedException">Trainer type is not supported.</exception>
public static POSModel Train(string languageCode, IObjectStream<POSSample> samples, TrainingParameters parameters, POSTaggerFactory factory, Monitor monitor) {
//int beamSize = trainParams.Get(Parameters.BeamSize, NameFinderME.DefaultBeamSize);
var contextGenerator = factory.GetPOSContextGenerator();
var manifestInfoEntries = new Dictionary<string, string>();
var trainerType = TrainerFactory.GetTrainerType(parameters);
switch (trainerType) {
case TrainerType.EventModelTrainer:
var es = new POSSampleEventStream(samples, contextGenerator);
var trainer = TrainerFactory.GetEventTrainer(parameters, manifestInfoEntries, monitor);
var eventModel = trainer.Train(es);
return new POSModel(languageCode, eventModel, manifestInfoEntries, factory);
case TrainerType.EventModelSequenceTrainer:
var ss = new POSSampleSequenceStream(samples, contextGenerator);
var trainer2 = TrainerFactory.GetEventModelSequenceTrainer(parameters, manifestInfoEntries, monitor);
var seqModel = trainer2.Train(ss);
return new POSModel(languageCode, seqModel, manifestInfoEntries, factory);
case TrainerType.SequenceTrainer:
var trainer3 = TrainerFactory.GetSequenceModelTrainer(parameters, manifestInfoEntries, monitor);
// TODO: This will probably cause issue, since the feature generator uses the outcomes array
var ss2 = new POSSampleSequenceStream(samples, contextGenerator);
var seqPosModel = trainer3.Train(ss2);
return new POSModel(languageCode, seqPosModel, manifestInfoEntries, factory);
default:
throw new NotSupportedException("Trainer type is not supported.");
}
}
