While looking at the source code of Malt Parser which actually has class LibLinear.java(jar file) and calls the java version of the liblinear toolkit; I don't find any option/way to return probability despite the information that, in principle training the model using liblinear(by default in malt parser) with Logistic regression(-s 0) should produce probability score of parsed trees.
The main concern is: Do the integration of Liblinear and Malt Parser working smoothly without affecting each other expected operations?
Working separately with Liblinear does give me probability output for the datasets.
liblinear-train -s 0 train_scale
//training data using logistic regression model
liblinear-predict -b 1 test_scale train_scale.model test_scale_output
//labels and classes and probability outputs. Here -b 1 does extract out probabilities of each datasets.
Malt parser works based on a transition system and 2 or three stacks. At each step a transition is predicted using liblinear or libsvm. The input to these models is composed of what is in the stacks and the current state of the machine. So making a decision at one step affects the rest of the possible decisions. To compute the probability of a tree would require to compute the aggregated probabilites of all trees (so that they sum up to 1), which is infeasable. You could compute a trust score of a tree, I guess, or of a particular arc, but it would be a trust score, not a probability. And afaik maltparser doesn't offer this out of the box. You would have to alter the source code, but it is do-able I think