A natural language parse ranker of a natural language processing (NLP) system
employs
a goodness function to rank the possible grammatically valid parses of an utterance.
The goodness function generates a statistical goodness measure (SGM) for each valid
parse. The parse ranker orders the parses based upon their SGM values. It presents
the parse with the greatest SGM values as the one that most likely represents the
intended meaning of the speaker. The goodness function of this parse ranker is
highly accurate in representing the intended meaning of a speaker. It also has
reasonable training data requirements. With the parse ranker, the SGM of a particular
parse is the combination of all of the probabilities of each node within the parse
tree of such parse. The probability at a given node is the probability of taking
a transition ("grammar rule") at that point. The probability at a node is conditioned
on highly predicative linguistic phenomena, such as "phrase levels," "null transitions,"
and "syntactic history".