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STOTSpecific Target Organ Toxicity
STOTShort Term Oxygen Therapy
STOTSymposium on Teaching Object Technology
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It can also be seen from this discussion that StOT does not predict strong ganging-up cumulativity.
StOT does not predict counting cumulativity either.
Goldwater and Johnson (2003) compare StOT with maximum entropy models (or, as they are sometimes called, log-linear models) that are state of the art by now in computational linguistics (see, for instance, Berger et al.
The general setup of a maximum entropy model is also quite similar to a StOT grammar.
As a side remark: (9) also illustrates another important difference between StOT and MaxEnt: [a.
There are learning algorithms both for StOT and for MaxEnt on the market that induce constraint rankings from corpora.
The absolute values of the StOT model and the MaxEnt model cannot really be compared because the evaluation procedure is different.
This StOT grammar corresponds to the probability distribution given in Figure 6a (for human possessors) and Figure 6b (for inanimate possessors).
As expected from the theoretical considerations in Section 2, StOT does not show counting cumulativity.
This variation is thus not predicted by the StOT model but it is a kind of noise.
Nonetheless, the fit of the data is better here than for the StOT model.
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