Linguistic disambiguation system and method using string-based pattern training to learn to resolve ambiguity sites
View Patent ↗A linguistic disambiguation system and method creates a knowledge base by training on patterns in strings that contain ambiguity sites. The string patterns are described by a set of reduced regular expressions (RREs) or very reduced regular expressions (VRREs). The knowledge base utilizes the RREs or VRREs to resolve ambiguity based upon the strings in which the ambiguity occurs. The system is trained on a training set, such as a properly labeled corpus. Once trained, the system may then apply the knowledge base to raw input strings that contain ambiguity sites. The system uses the RRE- and VRRE-based knowledge base to disambiguate the sites.
1. A system comprising:
means for defining a set of reduced regular expressions for particular patterns in strings, wherein the set of reduced regular expresssions has less expressiveness than a set of regular expressions; and
means for learning, from a training set, a knowledge base that uses the reduced regular expressions to resolve ambiguity based upon the strings in which the ambiguity occurs, wherein the learning means is configured to perform transformation sequence learning to create a set of rules that use the reduced regular expressions to resolve ambiguity based upon the strings in which the ambiguity occurs.
2. A system as recited in claim 1 , wherein the set of reduced regular expressions are defined over a finite alphabet Σ, wherein the alphabet is a union of multiple sets of distinct classes.
3. A system as recited in claim 1 , wherein the training set comprises a labeled corpus.
4. A system as recited in claim 1 , wherein the set of reduced regular expressions specify types of patterns that are allowed to be explored when learning from the training set.
5. A system as recited in claim 1 , wherein the learning means includes means for applying a set of very reduced regular expressions that are a proper subset of the reduced regular expressions.
6. A system comprising:
means for defining a set of reduced regular expressions for particular patterns in strings, wherein the set of reduced regular expressions has less expressiveness than a set of regular expressions; and
means for learning, from a training set, a knowledge base that uses the reduced regular expressions to resolve ambiguity based upon the strings in which the ambiguity occurs, wherein the set of reduced regular expressions specify types of patterns that are allowed to be explored when learning from the training set.
7. A system as recited in claim 6 , wherein the set of reduced regular expressions are defined over a finite alphabet Σ, wherein the alphabet is a union of multiple sets of distinct classes.
8. A system as recited in claim 6 , wherein the training set comprises a labeled corpus.
9. A system as recited in claim 6 , wherein the learning means comprises means for transformation sequence learning to create a set of rules that use the reduced regular expressions to resolve ambiguity based upon the strings in which the ambiguity occurs.
10. A system as recited in claim 6 , wherein the learning means includes means for applying a set of very reduced regular expressions that are a proper subset of the reduced regular expressions.
11. A system comprising:
means for receiving a string with an ambiguity site;
means for applying reduced regular expressions to describe a pattern in the string, wherein the reduced regular expressions:
are included in a knowledge base that is learned from a training set;
have less expressiveness than regular expressions; and
specify types of patterns that are allowed to be explored when the knowledge base is learned; and
selecting one of the reduced regular expressions to resolve the ambiguity site.
12. A system as recited in claim 11 , wherein the applying means is configured to apply a set of very reduced regular expressions that are a proper subset of the reduced regular expressions.
13. A system comprising means for:
receiving a string with an ambiguity site;
applying reduced regular expressions to describe a pattern in the string, wherein:
the applying includes applying a set of very reduced regular expressions that are a proper subset of the reduced regular expressions; and
the reduced regular expressions have less expressiveness than regular expressions; and
selecting one of the reduced regular expressions to resolve the ambiguity site.
14. A system comprising:
means for receiving a string with an ambiguity site;
means for applying reduced regular expressions to describe a pattern in the string, wherein the reduced regular expressions:
are included in a knowledge base that is learned from a training set;
have less expressiveness than regular expressions; and
specify types of patterns that are allowed to be explored when the knowledge base is learned; and
means for selecting one of the reduced regular expressions to resolve the ambiguity site.
15. A system as recited in claim 14 , wherein the applying means is configured to apply a set of very reduced regular expressions that are a proper subset of the reduced regular expressions.
16. A system comprising:
means for reading a training set;
means for constructing a graph having a root node that contains a primary position set of the training set and multiple paths from the root node to secondary nodes that represents a reduced regular expression that has less expressiveness than a regular expression, the secondary node containing a secondary position set to which the reduced regular expression maps;
means for scoring the secondary nodes to identify a particular secondary node; and
means for identifying the reduced regular expression that maps the path from the root node to the particular secondary node.
17. A training system comprising:
a memory to store a training set;
a processing unit; and
means, executable on the processing unit, for:
defining a set of reduced regular expressions for particular patterns in strings of the training set, wherein the set of reduced regular expressions has less expressiveness than a set of regular expressions; and
learning a knowledge base that uses the reduced regular expressions to describe the strings wherein the reduced regular expressions specify types of patterns that are allowed to be explored when the knowledge base is learned from the training set.
18. A training system as recited in claim 17 , wherein the training set comprises a labeled corpus.
19. A training system as recited in claim 17 , wherein the disambiguator trainer employs transformation sequence learning to create a set of rules that use the reduced regular expressions to describe the strings.
20. A system comprising:
a memory to store a knowledge base that uses reduced regular expressions to resolve ambiguity based upon strings in which the ambiguity occurs, wherein:
the knowledge base is learned from a training set using the reduced regular expressions;
the reduced regular expressions specify types of patterns that are allowed to be explored when the knowledge base is learned; and
the reduced regular expressions have less expressiveness than regular expressions;
a processing unit; and
means, executable on the processing unit, for:
receiving a string with an ambiguity site; and
applying a reduced regular expression from the knowledge base that describes a pattern in the string to resolve the ambiguity site.