/**
* @param previousGrammar
* @param previousLexicon
* @param grammar
* @param lexicon
* @param trainStateSetTrees
* @return
*/
public static double doOneEStep(
Grammar previousGrammar,
Lexicon previousLexicon,
Grammar grammar,
Lexicon lexicon,
StateSetTreeList trainStateSetTrees,
boolean updateOnlyLexicon,
int unkThreshold) {
boolean secondHalf = false;
ArrayParser parser = new ArrayParser(previousGrammar, previousLexicon);
double trainingLikelihood = 0;
int n = 0;
int nTrees = trainStateSetTrees.size();
for (Tree<StateSet> stateSetTree : trainStateSetTrees) {
secondHalf = (n++ > nTrees / 2.0);
boolean noSmoothing = true, debugOutput = false;
parser.doInsideOutsideScores(stateSetTree, noSmoothing, debugOutput); // E Step
double ll = stateSetTree.getLabel().getIScore(0);
ll =
Math.log(ll)
+ (100 * stateSetTree.getLabel().getIScale()); // System.out.println(stateSetTree);
if ((Double.isInfinite(ll) || Double.isNaN(ll))) {
if (VERBOSE) {
System.out.println("Training sentence " + n + " is given " + ll + " log likelihood!");
System.out.println(
"Root iScore "
+ stateSetTree.getLabel().getIScore(0)
+ " scale "
+ stateSetTree.getLabel().getIScale());
}
} else {
lexicon.trainTree(stateSetTree, -1, previousLexicon, secondHalf, noSmoothing, unkThreshold);
if (!updateOnlyLexicon) grammar.tallyStateSetTree(stateSetTree, previousGrammar); // E Step
trainingLikelihood += ll; // there are for some reason some sentences that are unparsable
}
}
lexicon.tieRareWordStats(unkThreshold);
// SSIE
((SophisticatedLexicon) lexicon).overwriteWithMaxent();
return trainingLikelihood;
}
/**
* This updates the inside-outside probabilities for the list of trees using the parser's
* doInsideScores and doOutsideScores methods.
*
* @param trees A list of binarized, annotated StateSet Trees.
* @param parser The parser to score the trees.
*/
public static void updateStateSetTrees(List<Tree<StateSet>> trees, ArrayParser parser) {
for (Tree<StateSet> tree : trees) {
parser.doInsideOutsideScores(tree, false, false);
}
}