Structured dictionary

• US 10,606,945 B2
• Filed: 04/19/2018
• Issued: 03/31/2020
• Est. Priority Date: 04/20/2015
• Status: Active Grant

• Current Assignee: Unified Compliance Framework
• Original Assignee: Unified Compliance Framework
• Inventors: Cougias, Dorian J., Zulch, Matthew, McEwen, Vicki, Rydell, Erwin, Granlund, Erik, Piliero, Steven
• Primary Examiner(s): Abebe, Daniel
• Application Number:
  US15/957,764
• Publication Number:
  US 20180253419A1
• Time in Patent Office: 712 Days
• Field of Search: 704 9
• CPC Class Codes: G06F 16/36 Creation of semantic tools, e.g. ontology or thesauri
• CPC Class Codes: G06F 16/367 Ontology
• CPC Class Codes: G06F 40/242 Dictionaries
• CPC Class Codes: G06F 40/247 Thesauruses; Synonyms
• CPC Class Codes: G06F 40/295 Named entity recognition
• CPC Class Codes: G06F 40/30 Semantic analysis

Abstract

A dictionary data structure is described. The data structure is made up of first, second, and third tables. The first table is comprised of entries each representing a natural language term, each entry of the first table containing a term ID identifying its term. The second table is comprised of entries each representing a definition, each entry of the second containing a definition ID identifying its definition. The third table is comprised of entries each representing correspondence between a terminate definition defining the term, each entry of the third table containing term ID identifying the defined term and a definition ID identifying the defining definition. The contents of the data structure are usable to identify any definitions corresponding to a term.

Claims

1. A computer implemented method for identifying one or more definitions for a distinguished natural language term, the method comprising:

identifying, by a computing system, among entries of a first table of an electronic database, each representing a natural language term, a first entry representing the distinguished natural language term;

identifying, by the computing system, among entries of a second table of the electronic database, each representing a correspondence between a term and a definition defining the term, one or more second entries related to the first entry;

for each particular second entry of the identified second entries, identifying, by the computing system, among entries of a third table of the electronic database, each representing a definition, a third entry related to the particular second entry, the third table being distinct from the second table;

for each of the identified entries of the third table, accessing, by the computing system in the identified entry of the third table a natural language representation of the definition represented by the entry of the third table; and

attributing, by the computing system writing to the electronic database, the accessed definition natural language representations to the distinguished natural language term.

2. The computer implemented method of claim 1 further comprising:

in relation to a distinguished one of the identified entries of the third table, identifying an entry of a fourth table corresponding to the distinguished entry of the third table,

wherein the identified entry of the fourth table represents a word type corresponding to the definition represented in the distinguished entry of the third table, and

wherein the word type specifies a part of speech for which a word is being used when it has the definition represented in the distinguished entry of the third table.

3. The computer implemented method of claim 1 further comprising:

identifying a fourth entry, from among entries of a fourth table, corresponding to both the first entry of the first table and a fifth entry of the first table,

wherein the identified fourth entry defines a hierarchical relationship between the distinguished natural language term of the first entry and another natural language term of the fifth entry.

4. The computer implemented method of claim 3, wherein the identified fourth entry includes a field defining a type of the hierarchical relationship.

5. The computer implemented method of claim 4, wherein the type of the hierarchical relationship corresponds to one of:

the distinguished natural language term being a type of the other natural language term;

the distinguished natural language term being part of the other natural language term;

the distinguished natural language term being a linguistic child of the other natural language term;

the distinguished natural language term being created by the other natural language term;

or

the distinguished natural language term being enforced by the other natural language term.

6. The computer implemented method of claim 3, wherein the identified fourth entry contains information indicating a source from which the hierarchical relationship defined in the identified fourth entry was derived.

7. The computer implemented method of claim 1 further comprising identifying one or more fourth entries, from among entries of a fourth table, corresponding to the first entry of the first table, wherein each identified fourth entry defines an alternate form of the distinguished natural language term.

8. The computer implemented method of claim 7 further comprising, for each particular fourth entry of the identified fourth entries, identifying, from among entries of a fifth table, a corresponding entry representing a type of difference that the particular fourth entry represents as compared to the first entry.

9. The computer implemented method of claim 1 further comprising identifying one or more fourth entries, from among entries of a fourth table, corresponding to the first entry of the first table, wherein each identified fourth entry identifies a term that is a synonym or antonym of the distinguished natural language term.

10. The computer implemented method of claim 1 further comprising identifying one or more fourth entries, from among entries of a fourth table, corresponding to the first entry of the first table, wherein each identified fourth entry defines an acronym of the distinguished natural language term.

11. The computer implemented method of claim 1, wherein the first table further includes a fourth entry representing another natural language term identified, through entries in the second and third tables, as having the same meaning as the distinguished natural language term;

wherein the fourth entry is designated as being a harmonized term; and

wherein, when the first table is accessed such that both the first and fourth entries are retrieved, the fourth entry is selected for preferred used due to the harmonized designation.

12. The computer implemented method of claim 1, wherein the identified third entries of the third table each relate to a control derived from an authority document.

13. The computer implemented method of claim 1 further comprising:

identifying, based on the attributed definition natural language representations, one or more relationships between the distinguished natural language term and one or more other natural language terms; and

wherein the identified one or more relationships are used in mapping portions of a document to controls.

14. A computer-readable storage medium, that is not a signal, storing data accessible by a program executable by a computing system, the computer-readable storage medium comprising:

a dictionary data structure, wherein the dictionary data structure includes information usable by the program to identify one or more definitions for a distinguished natural language term, the dictionary data structure comprising;

a first table comprising term entries, wherein each term entry represents a natural language term, and wherein a first entry of the term entries of the first table comprises a representation of the distinguished natural language term;

a second table comprising correspondence entries, wherein each correspondence entry represents a correspondence between a term and a definition defining the term, and wherein one or more second entries of the correspondence entries are related to the first entry; and

a third table comprising definition entries, wherein each definition entry represents a definition of a term, and wherein, for each particular second entry of the one or more second entries, the definition entries include a third entry related to the particular second entry,

wherein the second entries are useable by the program to identify the third entries, and each particular third entry of the identified third entries is useable by the program to attribute a representation of the definition represented by the particular third entry to the distinguished natural language term.

15. The computer-readable storage medium of claim 14, wherein the dictionary data structure further comprises a fourth table with hierarchy entries,

wherein each particular hierarchy entry corresponds to two of the term entries of the first table and defines a hierarchical relationship between the two natural language terms represented by the two term entries corresponding to the particular hierarchy entry, and wherein each particular hierarchy entry contains information indicating a source from which the hierarchical relationship defined in the particular hierarchy entry was derived.

16. The computer-readable storage medium of claim 14 wherein the dictionary data structure further comprises a fourth table with alternate form entries, wherein each alternate form entry corresponds to one of the term entries of the first table and defines an alternate form of the natural language term represented by the corresponding term entry, and

wherein the dictionary data structure further comprises a fifth table with same level entries, wherein each same level entry corresponds to one of the term entries of the first table and identifies a term that is a synonym or antonym of the natural language term represented by the corresponding term entry.

17. The computer-readable storage medium of claim 14, wherein the third entries of the third table each relate to a control derived from an authority document.

18. The computer-readable storage medium of claim 14,

wherein the program attributes the representations of the definitions represented by the third entries to the distinguished natural language term;

wherein the program identifies, based on the attributed representations of the definitions, one or more relationships between the distinguished natural language term and one or more other natural language terms; and

wherein the identified one or more relationships are used in mapping portions of a document to controls.

19. The computer-readable storage medium of claim 14, wherein the dictionary data structure is used by a computing system to augment a Part of Speech Tagger.

20. The computer-readable storage medium of claim 14, wherein the dictionary data structure is used by a computing system to augment a Named Entity Tagger.

21. The computer-readable storage medium of claim 14, wherein the dictionary data structure is used by a computing system to augment a Natural Language Processor.

22. A computing system for identifying one or more definitions for a distinguished natural language term, the computing system comprising:

one or more processors; and

memory storing instructions that, when executed by the one or more processors, cause the computing system to perform operations comprising;

identifying, among entries of a first table each representing a natural language term, a first entry representing the distinguished natural language term;

identifying, among entries of a second table each representing a correspondence between a term and a definition defining the term, one or more second entries related to the first entry;

for each particular second entry of the identified second entries, identifying, among entries of a third table each representing a definition, a third entry related to the particular second entry, the third table being distinct from the second table;

for each of the identified entries of the third table, accessing in the identified entry of the third table a natural language representation of the definition represented by the entry of the third table; and

attributing the accessed definition natural language representations to the distinguished natural language term.

23. The computing system of claim 22, wherein the operations further comprise:

in relation to a distinguished one of the identified entries of the third table, identifying an entry of a fourth table corresponding to the distinguished entry of the third table,

wherein the identified entry of the fourth table represents a word type corresponding to the definition represented in the distinguished entry of the third table, and

wherein the word type specifies a part of speech for which a word is being used when it has the definition represented in the distinguished entry of the third table.

24. The computing system of claim 22, wherein the operations further comprise:

identifying a fourth entry, from among entries of a fourth table, corresponding to both the first entry of the first table and a fifth entry of the first table,

wherein the identified fourth entry defines a hierarchical relationship between the distinguished natural language term of the first entry and another natural language term of the fifth entry.

25. The computing system of claim 24, wherein the identified fourth entry includes a field defining a type of the hierarchical relationship.

26. The computing system of claim 25, wherein the type of the hierarchical relationship corresponds to one of:

the distinguished natural language term being a type of the other natural language term;

the distinguished natural language term being part of the other natural language term;

the distinguished natural language term being a linguistic child of the other natural language term;

the distinguished natural language term being created by the other natural language term;

or

the distinguished natural language term being enforced by the other natural language term.

27. The computing system of claim 24, wherein the identified fourth entry contains information indicating a source from which the hierarchical relationship defined in the identified fourth entry was derived.

28. The computing system of claim 22, wherein the operations further comprise identifying one or more fourth entries, from among entries of a fourth table, corresponding to the first entry of the first table, wherein each identified fourth entry defines an alternate form of the distinguished natural language term.

29. The computing system of claim 28, wherein the operations further comprise, for each particular fourth entry of the identified fourth entries, identifying, from among entries of a fifth table, a corresponding entry representing a type of difference that the particular fourth entry represents as compared to the first entry.

30. The computing system of claim 22, wherein the operations further comprise identifying one or more fourth entries, from among entries of a fourth table, corresponding to the first entry of the first table, wherein each identified fourth entry identifies a term that is a synonym or antonym of the distinguished natural language term.

31. The computing system of claim 22, wherein the operations further comprise identifying one or more fourth entries, from among entries of a fourth table, corresponding to the first entry of the first table, wherein each identified fourth entry defines an acronym of the distinguished natural language term.

32. The computing system of claim 22, wherein the first table further includes a fourth entry representing another natural language term identified, through entries in the second and third tables, as having the same meaning as the distinguished natural language term;

wherein the fourth entry is designated as being a harmonized term; and

wherein, when the first table is accessed such that both the first and fourth entries are retrieved, the fourth entry is selected for preferred used due to the harmonized designation.

33. The computing system of claim 22, wherein the identified third entries of the third table each relate to a control derived from an authority document.

34. The computing system of claim 22, wherein the operations further comprise:

identifying, based on the attributed definition natural language representations, one or more relationships between the distinguished natural language term and one or more other natural language terms; and

wherein the identified one or more relationships are used in mapping portions of a document to controls.