Ranking Parser for a Natural Language Processing System

• US 20060106596A1
• Filed: 12/29/2005
• Published: 05/18/2006
• Est. Priority Date: 07/20/2000
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Weise, David N.
• Granted Patent: US 7,319,952 B2
• Time in Patent Office: Days
• US Class Current: 704/9
• CPC Class Codes: G06F 40/211 Syntactic parsing, e.g. based on context-free grammar [CFG] or unification grammars
• CPC Class Codes: G06F 40/216 using statistical methods

Abstract

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 value 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 this 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”

Claims

1. A computer-readable storage medium having computer-executable instructions that, when executed by a computer, perform a method to parse a phrase, the method comprising:

generating at least one parse tree representing a syntactically valid parse of the phrase, wherein the parse tree has hierarchical nodes;

calculating a syntactic history for each node.

2. One or more media as recited in claim 1 further comprising storing the syntactic history for each node.

3. One or more media as recited in claim 1, wherein the syntactic history may indicate one or more of the following syntactic phenomena:

passive verb phrase;

negative polarity;

domodal fronting;

comparative;

imperative;

topicalization of verb object.

4. A data structure for use with a computer having a processor and a memory, said structure comprising:

a corpus comprising one or more phrases in a natural language;

parse trees having hierarchical nodes, each tree representing at least one syntactically valid parse of each phrase in a subset of the corpus;

wherein one or more nodes have a syntactic history associated therewith.

5. A structure as recited in claim 4, wherein the subset of the corpus includes all phrases in the corpus.

6. A structure as recited in claim 4, wherein the syntactic history may indicate one or more of the following syntactic phenomena:

passive verb phrase;

negative polarity;

domodal fronting;

comparative;

imperative;

topicalization of verb object.

7. A method of parsing a phrase to facilitate processing of such phrase by a computer, the method comprising:

generating at least one parse tree representing a syntactically valid parse of the phrase, wherein the parse tree has hierarchical nodes;

calculating a syntactic history for each node.

8. A method as recited in claim 7 hither comprising storing the syntactic history for each node.

9. A method as recited in claim 7, wherein the syntactic history may indicate one or more of the following syntactic phenomena:

passive verb phrase;

negative polarity;

domodal fronting;

comparative;

imperative;

topicalization of verb object.