Abstract: A method of, and system for, generating a sentence from a semantic representation maps the semantic representation to an unordered set of syntactic nodes. Simplified generation grammar rules and statistical goodness measure values from a corresponding analysis grammar are then used to create a tree structure to order the syntactic nodes. The sentence is then generated from the tree structure. The generation grammar is a simplified (context free) version of a corresponding full (context sensitive) analysis grammar. In the generation grammar, conditions on each rule are ignored except those directly related to the semantic representation. The statistical goodness measure values, which are calculated through an analysis training phase in which a corpus of example sentences is processed using the full analysis grammar, are used to guide the generation choice to prefer substructures most commonly found in a particular syntactic/semantic context during analysis.

Abstract: A method and grammar checking system are provided that generate a stochastic score, or a statistical goodness measure, for each of an input string of text and one or more alternative strings of text. An alternative generator generates the alternative strings of text, and a ranking parser produces parse trees and corresponding statistical goodness measures for each of the strings. The string of text having the highest goodness measure is selected for recommendation to a user.

Abstract: A method of calculating trigram path probabilities for an input string of text containing a multi-word-entry (MWE) or a factoid includes tokenizing the input string to create a plurality of parse leaf units (PLUs). A PosColumn is constructed for each word, MWE, factoid and character in the input string of text which has a unique first (Ft) and last (Lt) token pair. TrigramColumns are constructed which define corresponding TrigramNodes each representing a trigram for three PosColumns. Forward and backward trigram path probabilities are calculated for each separate TrigramNode. The sums of all trigram path probabilities through each PLU are then calculated as a function of the forward and backward trigram path probabilities. Systems and computer-readable medium configured to implement the methods are also provided.

Abstract: A method of, and system for, generating a sentence from a semantic representation maps the semantic representation to an unordered set of syntactic nodes. Simplified generation grammar rules and statistical goodness measure values from a corresponding analysis grammar are then used to create a tree structure to order the syntactic nodes. The sentence is then generated from the tree structure. The generation grammar is a simplified (context free) version of a corresponding full (context sensitive) analysis grammar. In the generation grammar, conditions on each rule are ignored except those directly related to the semantic representation. The statistical goodness measure values, which are calculated through an analysis training phase in which a corpus of example sentences is processed using the full analysis grammar, are used to guide the generation choice to prefer substructures most commonly found in a particular syntactic/semantic context during analysis.

Abstract: A method and grammar checking system are provided that generate a stochastic score, or a statistical goodness measure, for each of an input string of text and one or more alternative strings of text. An alternative generator generates the alternative strings of text, and a ranking parser produces parse trees and corresponding statistical goodness measures for each of the strings. The string of text having the highest goodness measure is selected for recommendation to a user.

Abstract: A method of calculating trigram path probabilities for an input string of text containing a multi-word-entry (MWE) or a factoid includes tokenizing the input string to create a plurality of parse leaf units (PLUs). A PosColumn is constructed for each word, MWE, factoid and character in the input string of text which has a unique first (Ft) and last (Lt) token pair. TrigramColumns are constructed which define corresponding TrigramNodes each representing a trigram for three PosColumns. Forward and backward trigram path probabilities are calculated for each separate TrigramNode. The sums of all trigram path probabilities through each PLU are then calculated as a function of the forward and backward trigram path probabilities. Systems and computer-readable medium configured to implement the methods are also provided.

Abstract: A method of calculating trigram path probabilities for an input string of text containing a multi-word-entry (MWE) or a factoid includes tokenizing the input string to create a plurality of parse leaf units (PLUs). A PosColumn is constructed for each word, MWE, factoid and character in the input string of text which has a unique first (Ft) and last (Lt) token pair. TrigramColumns are constructed which define corresponding TrigramNodes each representing a trigram for three PosColumns. Forward and backward trigram path probabilities are calculated for each separate TrigramNode. The sums of all trigram path probabilities through each PLU are then calculated as a function of the forward and backward trigram path probabilities. Systems and computer-readable medium configured to implement the methods are also provided.

Abstract: A method and grammar checking system are provided that generate a stochastic score, or a statistical goodness measure, for each of an input string of text and one or more alternative strings of text. An alternative generator generates the alternative strings of text, and a ranking parser produces parse trees and corresponding statistical goodness measures for each of the strings. The string of text having the highest goodness measure is selected for recommendation to a user.

Abstract: A method of, and system for, generating a sentence from a semantic representation maps the semantic representation to an unordered set of syntactic nodes. Simplified generation grammar rules and statistical goodness measure values from a corresponding analysis grammar are then used to create a tree structure to order the syntactic nodes. The sentence is then generated from the tree structure. The generation grammar is a simplified (context free) version of a corresponding full (context sensitive) analysis grammar. In the generation grammar, conditions on each rule are ignored except those directly related to the semantic representation. The statistical goodness measure values, which are calculated through an analysis training phase in which a corpus of example sentences is processed using the full analysis grammar, are used to guide the generation choice to prefer substructures most commonly found in a particular syntactic/semantic context during analysis.

Abstract: An improved natural language parser uses a directed search template set to identify problematic word sequences, thus reducing processing time while increasing accuracy. The directed search template set is used to identify problematic input spans or portions of input spans. A problematic input span is one that contains at least one word or phrase that can be constructed in alternative ways. Problematic input spans can reduce the efficiency of a natural language parser and can result in the production of an inaccurate parse tree. Once a problematic span has been identified, the improved parser generates alternative parses for the problematic portion of the input span. This on-the-fly alternative parse generation permits the parser to consider the alternatives as early in the parse process as possible, thus reducing the overall time needed to parse a problematic input span.