Parsing Engine

Uses of Class
danbikel.parser.Transition

Packages that use Transition
danbikel.parser Provides the core framework of this extensible statistical parsing engine. 
 

Uses of Transition in danbikel.parser
 

Fields in danbikel.parser declared as Transition
 Transition[] ProbabilityStructure.transitions
          A reusable Transition array to store transitions.
 

Methods in danbikel.parser that return Transition
 Transition Transition.copy()
          Returns a deep copy of this Transition object.
 Transition Transition.copyCanonical(Map canonicalFutures, Map canonicalHistories)
          Returns a copy of this object with canonical versions of the history and future events.
protected static Transition Model.getCanonical(Transition trans, FlexibleMap canonical)
          This method assumes trans already contains a canonical history and a canonical future.
 Transition ProbabilityStructure.getTransition(TrainerEvent trainerEvent, int backOffLevel)
          Returns the reusable transition object for the specified back-off level, with its history set to the result of calling getHistory(trainerEvent, backOffLevel) and its future the result of getFuture(trainerEvent, backOffLevel).
protected  Transition[] Model.getTransitions(Transition zeroLevelTrans, Transition[] trans)
          Inserts the Transition objects representing conditional events for all back-off levels of this model into the specified array, with trans[0] = zeroLevelTrans.
 

Methods in danbikel.parser with parameters of type Transition
protected  double Model.estimateLogProbUsingPrecomputed(Transition transition, int atLevel)
          Estimates the log prob of the specified transition using precomputed probabilities and lambdas and Model.histBackOffMap (debugging method).
protected static Transition Model.getCanonical(Transition trans, FlexibleMap canonical)
          This method assumes trans already contains a canonical history and a canonical future.
static double[] AnalyzeDisns.getLogProbDisn(Model model, int level, Event hist, Set futures, double[] disn, Transition tmpTrans)
          Returns the smoothed log-probability distribution for the specified history at the specified back-off level in the specified model.
protected  Transition[] Model.getTransitions(Transition zeroLevelTrans, Transition[] trans)
          Inserts the Transition objects representing conditional events for all back-off levels of this model into the specified array, with trans[0] = zeroLevelTrans.
protected  Transition[] Model.getTransitions(Transition zeroLevelTrans, Transition[] trans)
          Inserts the Transition objects representing conditional events for all back-off levels of this model into the specified array, with trans[0] = zeroLevelTrans.
protected  void InterpolatedKnesserNeyModel.precomputeProbs(MapToPrimitive.Entry transEntry, double[] lambdas, double[] estimates, Transition[] transitions, Event[] histories, int lastLevel)
           
protected  void Model.precomputeProbs(MapToPrimitive.Entry transEntry, double[] lambdas, double[] estimates, Transition[] transitions, Event[] histories, int lastLevel)
          Precomputes the probabilities and smoothing values for the Transition object contained as a key within the specified map entry, where the value is the count of the transition.
protected  void InterpolatedKnesserNeyModel.precomputeProbs(TrainerEvent event, Transition[] transitions, Event[] histories)
          Deprecated. This method is called by Model.precomputeProbs(CountsTable,Filter), which is also deprecated.
protected  void Model.precomputeProbs(TrainerEvent event, Transition[] transitions, Event[] histories)
          Deprecated. This method is called by Model.precomputeProbs(CountsTable,Filter), which is also deprecated.
static void PrintDisn.printLogProbDisn(PrintWriter writer, ModelCollection mc, Model model, int level, Event hist, Set futures, Transition tmpTrans)
          Prints the log-probability distribution of the specified event at the specified back-off level of the specified model to the specified writer.
 boolean ProbabilityStructure.removeTransition(int backOffLevel, Transition transition)
          Returns true if the specified transition contains either a history or future for which ProbabilityStructure.removeHistory(int,Event) or ProbabilityStructure.removeFuture(int,Event) returns true, respectively.
protected  void InterpolatedKnesserNeyModel.storePrecomputedProbs(double[] lambdas, double[] estimates, Transition[] transitions, Event[] histories, int lastLevel)
           
protected  void Model.storePrecomputedProbs(double[] lambdas, double[] estimates, Transition[] transitions, Event[] histories, int lastLevel)
          Stores the specified smoothing values (lambdas) and smoothed probability estimates in the Model.precomputedProbs and Model.smoothingParams map arrays.
 


Parsing Engine

Author: Dan Bikel.