/// <summary>
/// Creates a new event array based on the outcomes predicted by the specified parameters for the specified sequence.
/// </summary>
/// <param name="sequence">The sequence to be evaluated.</param>
/// <param name="model">The model.</param>
/// <returns>The event array.</returns>
public Event[] UpdateContext(Sequence sequence, AbstractModel model)
{
var tagger = new POSTaggerME(new POSModel("x-unspecified", model, null, new POSTaggerFactory()));
var sample = sequence.GetSource <POSSample>();
var tags = tagger.Tag(sample.Sentence);
return(POSSampleEventStream.GenerateEvents(
sample.Sentence,
tags,
Array.ConvertAll(sample.AdditionalContext, input => (object)input),
contextGenerator).ToArray());
}
/// <summary>
/// Creates a new event array based on the outcomes predicted by the specified parameters for the specified sequence.
/// </summary>
/// <param name="sequence">The sequence to be evaluated.</param>
/// <param name="model">The model.</param>
/// <returns>The event array.</returns>
public Event[] UpdateContext(Sequence sequence, AbstractModel model)
{
var tagger =
new NameFinderME(
new TokenNameFinderModel("x-unspecified", model, new Dictionary <string, object>(), null));
var sentence = sequence.GetSource <NameSample>().Sentence;
var tags = seqCodec.Encode(tagger.Find(sentence), sentence.Length);
return(NameFinderEventStream.GenerateEvents(sentence, tags, pcg).ToArray());
}
/// <summary>
/// Creates a new event array based on the outcomes predicted by the specified parameters for the specified sequence.
/// </summary>
/// <param name="sequence">The sequence to be evaluated.</param>
/// <param name="model">The model.</param>
/// <returns>The event array.</returns>
public Event[] UpdateContext(Sequence sequence, AbstractModel model)
{
/*
* var tagger = new NameFinderME(new TokenNameFinderModel("x-unspecified", model, new Dictionary<string, string>(), null));
*
* String[] sentence = sequence.GetSource<NameSample>().Sentence;
*
* String[] tags = seqCodec.Encode(tagger.Find(sentence), sentence.Length);
* Event[] events = new Event[sentence.length];
*
* NameFinderEventStream.GenerateEvents(sentence,tags,pcg).toArray(events);
*
* return events;
*/
throw new NotImplementedException();
}
/// <summary>
/// Creates a new event array based on the outcomes predicted by the specified parameters for the specified sequence.
/// </summary>
/// <param name="sequence">The sequence to be evaluated.</param>
/// <param name="model">The model.</param>
/// <returns>The event array.</returns>
public Event[] UpdateContext(Sequence sequence, AbstractModel model) {
var tagger =
new NameFinderME(
new TokenNameFinderModel("x-unspecified", model, new Dictionary<string, object>(), null));
var sentence = sequence.GetSource<NameSample>().Sentence;
var tags = seqCodec.Encode(tagger.Find(sentence), sentence.Length);
return NameFinderEventStream.GenerateEvents(sentence, tags, pcg).ToArray();
}
public Event[] UpdateContext(Sequence sequence, AbstractModel model)
{
// TODO: Should be implemented for Perceptron sequence learning ...
return(null);
}
/// <summary>
/// Creates a new event array based on the outcomes predicted by the specified parameters for the specified sequence.
/// </summary>
/// <param name="sequence">The sequence to be evaluated.</param>
/// <param name="model">The model.</param>
/// <returns>The event array.</returns>
/// <remarks>Always return null.</remarks>
public Event[] UpdateContext(Sequence sequence, AbstractModel model) {
// TODO: Should be implemented for Perceptron sequence learning ...
return null;
}
/// <summary>
/// Creates a new event array based on the outcomes predicted by the specified parameters for the specified sequence.
/// </summary>
/// <param name="sequence">The sequence to be evaluated.</param>
/// <param name="model">The model.</param>
/// <returns>The event array.</returns>
public Event[] UpdateContext(Sequence sequence, AbstractModel model) {
var tagger = new POSTaggerME(new POSModel("x-unspecified", model, null, new POSTaggerFactory()));
var sample = sequence.GetSource<POSSample>();
var tags = tagger.Tag(sample.Sentence);
return POSSampleEventStream.GenerateEvents(
sample.Sentence,
tags,
Array.ConvertAll(sample.AdditionalContext, input => (object) input),
contextGenerator).ToArray();
}