internal static List <Event> GenerateEvents(String[] sentence, String[] outcomes, INameContextGenerator cg)
{
var events = new List <Event>(outcomes.Length);
for (int i = 0; i < outcomes.Length; i++)
{
events.Add(new Event(outcomes[i], cg.GetContext(i, sentence, outcomes, null)));
}
cg.UpdateAdaptiveData(sentence, outcomes);
return(events);
}
/// <summary>
/// Generates name tags for the given sequence, typically a sentence, returning token spans for any identified names.
/// </summary>
/// <param name="tokens">An array of the tokens or words of the sequence, typically a sentence.</param>
/// <param name="additionalContext">Features which are based on context outside of the sentence but which should also be used.</param>
/// <returns>An array of spans for each of the names identified.</returns>
public Span[] Find(string[] tokens, string[][] additionalContext)
{
additionalContextFeatureGenerator.SetCurrentContext(additionalContext);
bestSequence = model.BestSequence(tokens,
Array.ConvertAll(additionalContext, input => (object)input),
contextGenerator,
sequenceValidator);
var outcomes = bestSequence.Outcomes.ToArray();
contextGenerator.UpdateAdaptiveData(tokens, outcomes);
var spans = sequenceCodec.Decode(outcomes);
var probs = Probs(spans);
for (var i = 0; i < probs.Length; i++)
{
spans[i].Probability = probs[i];
}
return(spans);
}