Enabling rhetorical analysis via the use of communicative discourse trees

• US 10,796,102 B2
• Filed: 05/09/2018
• Issued: 10/06/2020
• Est. Priority Date: 05/10/2017
• Status: Active Grant

• Current Assignee: Oracle International Corporation (Oracle Corporation)
• Original Assignee: Oracle International Corporation (Oracle Corporation)
• Inventors: Galitsky, Boris
• Primary Examiner(s): Spooner, Lamont M
• Application Number:
  US15/975,683
• Publication Number:
  US 20180329879A1
• Time in Patent Office: 881 Days
• Field of Search: 704 1, 704 9, 704 10
• CPC Class Codes: G06F 16/322 Trees
• CPC Class Codes: G06F 16/3329 Natural language query formulation or dialogue systems
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures
• CPC Class Codes: G06F 40/211 Syntactic parsing, e.g. based on context-free grammar [CFG] or unification grammars
• CPC Class Codes: G06F 40/35 Discourse or dialogue representation
• CPC Class Codes: G06F 40/44 Statistical methods, e.g. probability models
• CPC Class Codes: G06F 40/51 Translation evaluation
• CPC Class Codes: G06F 40/55 Rule-based translation
• CPC Class Codes: G06N 3/08 Learning methods

Abstract

Systems, devices, and methods of the present invention calculate a rhetorical relationship between one or more sentences. In an example, a computer-implemented method accesses a sentence comprising a plurality of fragments. At least one fragment includes a verb and a words. Each word includes a role of the words within the fragment. Each fragment is an elementary discourse unit. The method generates a discourse tree that represents rhetorical relationships between the sentence fragments. The discourse tree includes nodes including nonterminal and terminal nodes, each nonterminal node representing a rhetorical relationship between two of the sentence fragments, and each terminal node of the nodes of the discourse tree is associated with one of the sentence fragments. The method matches each fragment that has a verb to a verb signature, thereby creating communicative discourse tree.

Claims

1. A computer-implemented method comprising:

accessing a sentence comprising a plurality of fragments, wherein at least one fragment comprises a verb and a plurality of words, each word comprising a role of the words within the fragment, wherein each fragment is an elementary discourse unit;

generating a discourse tree that represents rhetorical relationships between the plurality of fragments, wherein the discourse tree comprises a plurality of nodes, each nonterminal node representing a rhetorical relationship between two of the plurality of fragments, each terminal node of the nodes of the discourse tree is associated with one of the plurality of fragments;

matching each fragment that has a verb to a verb signature, thereby creating a communicative discourse tree, the matching comprising;

accessing a plurality of verb signatures, wherein each verb signature comprises the verb of a fragment and a sequence of thematic roles, wherein each thematic role describes a respective relationship between the verb and related words;

determining, for each verb signature of the plurality of verb signatures, a plurality of thematic roles of the respective verb signature, wherein each of the thematic roles matches a role of a word in the fragment;

selecting a particular verb signature from the plurality of verb signatures based on the particular verb signature comprising a highest number of matches of roles; and

associating the particular verb signature with the fragment;

identifying a correspondence between the communicative discourse tree and an additional communicative discourse tree from a plurality of communicative discourse trees; and

sending text associated with the additional communicative discourse tree to an external device.

2. The method of claim 1, wherein the sentence is a question received from the external device, the method further comprising:

accessing a plurality of candidate answers; and

determining the plurality of communicative discourse trees by creating, for each candidate answer of the plurality of candidate answers, a respective communicative discourse tree.

3. The method of claim 1, wherein the associating further comprises:

identifying each of the plurality of thematic roles in the particular verb signature; and

matching, for each of the plurality of thematic roles in the particular verb signature, a corresponding word in the fragment to the thematic role.

4. The method of claim 1, further comprising:

identifying, from the plurality of fragments, a first fragment and a second fragment, the first fragment having a first verb signature and the second fragment having a second verb signature, wherein the first verb signature comprises a thematic role;

determining that the second fragment corresponds to the thematic role of the first fragment; and

associating a nonterminal node with an updated first verb signature comprising the first verb signature and the second verb signature.

5. The method of claim 1, wherein the verb is a communicative verb.

6. The method of claim 1, wherein each verb signature of the plurality of verb signatures comprises one of (i) an adverb, (ii) a noun phrase, or (iii) a noun.

7. The method of claim 1, wherein the identifying comprises:

merging the additional communicative discourse tree with the communicative discourse tree; and

computing a level of complementarity between the additional communicative discourse tree and the communicative discourse tree by applying a predictive model to the merged communicative discourse tree.

8. The method of claim 7, wherein the predictive model is a machine learning algorithm that is trained to determine a level of complementarity between two communicative discourse trees identified as matching or not matching.

9. A non-transitory computer-readable storage medium storing computer-executable program instructions, wherein when executed by a processing device, the program instructions cause the processing device to perform operations comprising:

accessing a sentence comprising a plurality of fragments, wherein at least one fragment comprises a verb and a plurality of words, each word comprising a role of the words within the fragment, wherein each fragment is an elementary discourse unit;

generating a discourse tree that represents rhetorical relationships between the plurality of fragments, wherein the discourse tree comprises a plurality of nodes, each nonterminal node representing a rhetorical relationship between two of the plurality of fragments, each terminal node of the nodes of the discourse tree is associated with one of the plurality of fragments;

matching each fragment that has a verb to a verb signature, thereby creating a communicative discourse tree, the matching comprising;

accessing a plurality of verb signatures, wherein each verb signature comprises the verb of a fragment and a sequence of thematic roles, wherein each thematic role describes a respective relationship between the verb and related words;

determining, for each verb signature of the plurality of verb signatures, a plurality of thematic roles of the respective verb signature, wherein each of the thematic roles matches a role of a word in the fragment;

selecting a particular verb signature from the plurality of verb signatures based on the particular verb signature comprising a highest number of matches of roles; and

associating the particular verb signature with the fragment;

identifying a complementarity between the communicative discourse tree and an additional communicative discourse tree from a plurality of communicative discourse trees; and

sending text associated with the additional communicative discourse tree to an external device.

10. The non-transitory computer-readable storage medium of claim 9, the operations further comprising:

receiving, from the external device, a request comprising a question;

accessing a plurality of candidate answers;

determining a plurality of candidate answer communicative discourse trees by creating, for each candidate answer of the plurality of candidate answers, a communicative discourse tree;

determining, for each of the candidate answers, a score based on a comparison between a respective candidate answer communicative discourse tree and the communicative discourse tree; and

providing, to the external device, an answer corresponding to the communicative discourse tree with a highest score.

11. The non-transitory computer-readable storage medium of claim 9, wherein the associating further comprises:

identifying each of the plurality of thematic roles in the particular verb signature; and

matching, for each of the plurality of thematic roles in the particular verb signature, a corresponding word in the fragment to the thematic role.

12. The non-transitory computer-readable storage medium of claim 9, the operations further comprising:

identifying, from the plurality of fragments, a first fragment and a second fragment, the first fragment having a first signature and the second fragment having a second signature, wherein the first signature comprises a thematic role;

determining that the second fragment corresponds to the thematic role of the first fragment; and

associating a nonterminal node with an updated first signature comprising the first signature and the second signature.

13. The non-transitory computer-readable storage medium of claim 9, wherein the verb is a communicative verb.

14. The non-transitory computer-readable storage medium of claim 9, wherein each verb signature of the plurality of verb signatures comprises one of (i) an adverb, (ii) a noun phrase, or (iii) a noun.

15. The non-transitory computer-readable storage medium of claim 9, wherein the identifying comprises:

merging the additional communicative discourse tree with the communicative discourse tree; and

computing a level of complementarity between additional communicative discourse tree and the communicative discourse tree by applying a predictive model to the merged communicative discourse tree.

16. A system comprising:

a non-transitory computer-readable medium storing computer-executable program instructions; and

a processing device communicatively coupled to the non-transitory computer-readable medium for executing the computer-executable program instructions, wherein executing the computer-executable program instructions configures the processing device to perform operations comprising;

accessing a sentence comprising a plurality of fragments, wherein at least one fragment comprises a verb and a plurality of words, each word comprising a role of the words within the fragment, wherein each fragment is an elementary discourse unit, and wherein the sentence corresponds to a question;

generating a discourse tree that represents rhetorical relationships between the plurality of fragments, wherein the discourse tree comprises a plurality of nodes, each nonterminal node representing a rhetorical relationship between two of the plurality of fragments, each terminal node of the nodes of the discourse tree is associated with one of the plurality of fragments;

matching each fragment that has a verb to a verb signature, thereby creating a communicative discourse tree, the matching comprising;

accessing a plurality of verb signatures, wherein each verb signature comprises the verb of a fragment and a sequence of thematic roles, wherein a thematic role describes a relationship between the verb and related words;

determining, for each verb signature of the plurality of verb signatures, a plurality of thematic roles of the respective signature, wherein each of the thematic roles matches a role of a word in the fragment;

selecting a particular verb signature from the plurality of verb signatures based on the particular verb signature comprising a highest number of matches; and

associating the particular verb signature with the fragment;

determining a plurality of candidate answer communicative discourse trees by creating, for each candidate answer of a plurality of candidate answers, a candidate answer communicative discourse tree;

determining, for each of the candidate answers, a score based on a comparison between a respective candidate answer communicative discourse tree and the communicative discourse tree; and

providing, to a device, an answer corresponding to the candidate answer communicative discourse tree with a highest score.

17. The system of claim 16, wherein the associating further comprises:

identifying each of the plurality of thematic roles in the particular verb signature; and

matching, for each of the plurality of thematic roles in the particular verb signature, a corresponding word in the fragment to the thematic role.

18. The system of claim 16, further comprising:

identifying, from the plurality of fragments, a first fragment and a second fragment, the first fragment having a first verb signature and the second fragment having a second verb signature, and wherein the first verb signature comprises a thematic role;

determining that the second fragment corresponds to the thematic role of the first fragment; and

associating a nonterminal node with an updated first verb signature comprising the first verb signature and the second verb signature.

19. The system of claim 16, wherein the verb is a communicative verb.

20. The system of claim 16, wherein determining the score comprises computing a level of complementarity between the respective candidate answer communicative discourse tree and the communicative discourse tree by applying a predictive model to the merged communicative discourse tree.