Processing natural language arguments and propositions

1. A method for processing natural language arguments, the method comprising:

receiving a set of natural language input;

associating a proposition tag with a first portion of the natural language input identified as including a first proposition, the proposition tag linking the first portion of the natural language input to an emotionally neutral proposition value;

associating a rhetorical argument type with a second portion of the natural language input, the associated rhetorical argument type identified based on rules for determining an amount of support for an argument that a proposition provides;

tabulating a conclusion based on the first proposition and the identified rhetorical argument type; and

generating a map of the set of natural language input for display, wherein the map visually illustrates that the first portion of the natural language input associated with the proposition tag and that the second portion of the natural language input is associated with the identified rhetorical argument type.

2. The method of claim 1 , further comprising:

associating a second proposition tag with a third portion of the natural language input identified as including a second proposition, the second proposition tag linking the third portion of the natural language input to a second emotionally neutral proposition value;

organizing the first proposition and the second proposition based on the identified rhetorical argument type; and

identifying an interrelationship between the first proposition and the second proposition.

3. The method of claim 1 , further comprising locating the first proposition within a proposition taxonomy, the first proposition taxonomy comprising a plurality of hierarchically-organized propositions, wherein the map is a proposition flow tree comprising a neighbor proposition and the first proposition, the neighbor proposition adjacent to the first proposition within the proposition taxonomy.

4. The method of claim 3 , further comprising identifying an interrelationship between the first proposition and the neighbor proposition, the interrelationship reflecting an effect that a likelihood of truth of the neighbor proposition has on a likelihood of truth of the first proposition.

5. The method of claim 3 , further comprising identifying a proposition conflict based on the proposition flow tree, the proposition conflict comprising two or more incompatible propositions within the proposition flow tree.

6. The method of claim 5 , further comprising evaluating the two or more incompatible propositions to identify a respective likelihood of truth.

7. The method of claim 1 , further comprising:

identifying an agent of the natural language input and an object of the natural language input, the agent impacting the object;

identifying an incentive of the agent;

determining a core value of the agent based on the incentive and the object; and

generating a component of persuasive leverage based on one of the core value, the incentive, and the object.

8. The method of claim 1 , wherein the map further includes at least one flag indicating a burden of proof associated with the first proposition.

9. The method of claim 1 , wherein the rhetorical argument type corresponds to a rhetorical principle, and wherein the rhetorical argument type is based on whether the rhetorical principle is violated by the argument in relation to the proposition.

10. The method of claim 9 , wherein the rhetorical principle is associated with at least one of fact being contradicted, argument by analogy, category mismatch, solution being proposed, consequence being asserted, outcome different from intent, topic shift or splitting, non-sequitur, questions of degree, confusion of subject agency or affected parties, assignment of burden of proof, question begging, or incompleteness of a set.

11. A system for processing natural language arguments, the system comprising:

a user interface that receives a set of natural language input;

a processor that executes instructions stored in memory, wherein execution of the instructions by the processor:

associates a proposition tag with a first portion of the natural language input identified as including a first proposition, the proposition tag linking the first portion of the natural language input to an emotionally neutral proposition value;

associates a rhetorical argument type with a second portion of the natural language input, the associated rhetorical argument type identified based on rules for determining an amount of support for an argument that a proposition provides;

tabulates a conclusion based on the first proposition and the identified rhetorical argument type; and

generates a map of the set of natural language input for display, wherein the map visually illustrates that the first portion of the natural language input associated with the proposition tag and that the second portion of the natural language input is associated with the identified rhetorical argument type; and

a display screen that displays the generated map.

12. The system of claim 11 , wherein the processor executes further instructions to:

associate a second proposition tag with a third portion of the natural language input identified as including a second proposition, the second proposition tag linking the third portion of the natural language input to a second emotionally neutral proposition value;

organize the first proposition and the second proposition based on the identified rhetorical argument type; and

identify an interrelationship between the first proposition and the second proposition.

13. The system of claim 11 , wherein the processor executes further instructions to locate the first proposition within a proposition taxonomy, the first proposition taxonomy comprising a plurality of hierarchically-organized propositions, wherein the map is a proposition flow tree comprising a neighbor proposition and the first proposition, the neighbor proposition adjacent to the proposition within the proposition taxonomy.

14. The system of claim 13 , wherein the processor executes further instructions to identify an interrelationship between the first proposition and the neighbor proposition, the interrelationship reflecting an effect that a likelihood of truth of the neighbor proposition has on a likelihood of truth of the first proposition.

15. The system of claim 13 , wherein the processor executes further instructions to identify a proposition conflict based on the proposition flow tree, the proposition conflict comprising two or more incompatible propositions within the proposition flow tree.

16. The system of claim 15 , wherein the processor executes further instructions to evaluate the two or more incompatible propositions to identify a respective likelihood of truth.

17. The system of claim 11 , wherein the processor executes further instructions to:

identify an agent of the natural language input and an object of the natural language input, the agent impacting the object;

identify an incentive of the agent;

determine a core value of the agent based on the incentive and the object; and

generate a component of persuasive leverage based on one of the core value, the incentive, and the object.

18. The system of claim 11 , wherein the map further includes at least one flag indicating a burden of proof associated with the first proposition.

19. A non-transitory computer-readable storage medium, having embodied thereon a program executable by a processor to perform a method for processing natural language arguments, the method comprising:

receiving a set of natural language input;

associating a proposition tag with a first portion of the natural language input identified as including a first proposition, the proposition tag linking the first portion of the natural language input to an emotionally neutral proposition value;

associating a rhetorical argument type with a second portion of the natural language input, the associated rhetorical argument type identified based on rules for determining an amount of support for an argument that a proposition provides;

tabulating a conclusion based on the first proposition and the identified rhetorical argument type; and

generating a map of the set of natural language input for display, wherein the map visually illustrates that the first portion of the natural language input associated with the proposition tag and that the second portion of the natural language input is associated with the identified rhetorical argument type.