ROBUST REVERSIBLE FINITE-STATE APPROACH TO CONTEXTUAL GENERATION AND SEMANTIC PARSING
First Claim
1. A method of providing for analysis and generation through a same probabilistic model, comprising:
- providing a reversible probabilistic model comprising a set of factors comprising;
a canonical factor which is a function of a logical form and a realization;
a similarity factor, which is a function of a canonical text string and a surface string,a language model factor, which is a static function of a surface string,a language context factor, which is a dynamic function of a surface string, anda semantic context factor, which is a dynamic function of a logical form;
the reversible probabilistic model being able to perform both analysis and generation,wherein in performing generation, the canonical factor, similarity factor, language model factor, and language context factor are composed to receive as input a logical form selected from a set of logical forms and output at least one surface string, andwherein in performing analysis, the similarity factor, canonical factor, and semantic context factor are composed to take as input a surface string and output at least one logical form in a set of logical forms, andwherein the performing of the analysis and generation is implemented by a processor.
2 Assignments
0 Petitions
Accused Products
Abstract
A system and method permit analysis and generation to be performed with the same reversible probabilistic model. The model includes a set of factors, including a canonical factor, which is a function of a logical form and a realization thereof, a similarity factor, which is a function of a canonical text string and a surface string, a language model factor, which is a static function of a surface string, a language context factor, which is a dynamic function of a surface string, and a semantic context factor, which is a dynamic function of a logical form. When performing generation, the canonical factor, similarity factor, language model factor, and language context factor are composed to receive as input a logical form and output a surface string, and when performing analysis, the similarity factor, canonical factor, and semantic context factor are composed to take as input a surface string and output a logical form.
11 Citations
20 Claims
-
1. A method of providing for analysis and generation through a same probabilistic model, comprising:
-
providing a reversible probabilistic model comprising a set of factors comprising; a canonical factor which is a function of a logical form and a realization; a similarity factor, which is a function of a canonical text string and a surface string, a language model factor, which is a static function of a surface string, a language context factor, which is a dynamic function of a surface string, and a semantic context factor, which is a dynamic function of a logical form; the reversible probabilistic model being able to perform both analysis and generation, wherein in performing generation, the canonical factor, similarity factor, language model factor, and language context factor are composed to receive as input a logical form selected from a set of logical forms and output at least one surface string, and wherein in performing analysis, the similarity factor, canonical factor, and semantic context factor are composed to take as input a surface string and output at least one logical form in a set of logical forms, and wherein the performing of the analysis and generation is implemented by a processor. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18)
-
-
19. A system for performing analysis and generation comprising:
-
memory which stores a reversible probabilistic model comprising a set finite state machines comprising; a canonical finite state machine, which is a function of a logical form and a canonical text string which is a realization of the logical form; a similarity finite state machine, which is a function of a canonical text string and a surface string, a language model finite state machine which is a static function of a surface string, a language context finite state machine, which is a dynamic function of a surface string, and a semantic context finite state machine, which is a dynamic function of a logical form; a dialog manager which inputs logical forms and surface strings to the reversible probabilistic model for performing analysis and generation, wherein in performing generation the canonical finite state machine, similarity finite state machine, language model finite state machine, and language context finite state machine of the reversible probabilistic model are composed to receive as input a logical form selected from a set of logical forms and output at least one surface string, and wherein in performing analysis, the similarity finite state machine, canonical finite state machine, and semantic context finite state machine of the reversible probabilistic model are composed to take as input a surface string and output at least one logical form in a set of logical forms, and a processor which implements the dialog manager.
-
-
20. A computer implemented method for conducting a dialog comprising:
-
providing in computer memory a reversible probabilistic model able to perform both analysis and generation, the reversible probabilistic model comprising a set of finite state machines comprising; a canonical finite state machine, which is a function of a logical form and a canonical text string, which is a realization of the logical form; a similarity finite state machine, which is a function of a canonical text string and a surface string, a language model finite state machine which is a static function of a surface string, a language context finite state machine, which is a dynamic function of a surface string; and a semantic context finite state machine, which is a dynamic function of a logical form; receiving a surface text string uttered by a person; analyzing the received surface text string, wherein in the analysis, the similarity factor, canonical factor, and semantic context factor are composed to take as input the surface string and output a first of a set of logical forms, and selecting a second logical form based on the first logical form; generating at least one surface string, wherein in the generation, the canonical factor, similarity factor, language model factor, and language context factor are composed to receive as input the second logical form and output at least one surface string; and outputting one of the at least one surface string or a surface string derived therefrom for communication to the person on a computing device, wherein the analyzing and generation are implemented by a processor.
-
Specification