Input: sentence
Output: labelIndexes, featureIDs/Values through positionFeaturePairs
We want to yield a sequence of (t, featID, featValue) pairs,
to be conjuncted against label IDs at position t.
This contains
(1) Feature and label vocabularies (therefore knowledge of numberization)
(2) Model coefficients (and knowledge how to flattenize them for LBFGS's sake)
(3) Decoding/posterior and gradient computation
Model() - Constructor for class cmu.arktweetnlp.impl.Model
One sequence structure -- typically, for one sentence
This is the model's view of a sentence -- only deals with non-textual numberized versions of everything
Implementation of the (Michelot 1986) technique for projecting
a real vector into the feasible region K defined by the following constraints:
- components must sum to 1, and
- they must be nonnegative.