Logic-based controlled natural languages usually provide some facility for compositional representation, minimally including sentence level coordination and sometimes subordination. Although these compositional forms suffice for representing short passages, they can become unwieldy for expressing entire paragraphs and documents. This paper describes an approach to representing larger composite texts in a controlled natural language. This approach, called discourse-based reasoning, integrates rhetorical structure theory with argumentation theory to define a model for defining composite structures and argument strategies in an ontological representation. Rhetorical structures are used to represent controlled texts, and argument strategies are defined for reasoning about interactions between structures. This provides the basis for expressing, summarizing, and interacting with explanatory and argumentative discourse. This would expand the scope of problems that may be addressed using controlled natural languages.
Logic-based controlled natural languages usually provide some facility for
compositional representation. Most well known among these, ACE and PENG define
discourse representation structures that support both sentence level coordination and
subordination [
Our approach, called Discourse-Based Reasoning (DBR), is based on underlying
structures of natural discourse and argumentation theory. DBR draws on Mann and
Thompson's Rhetorical Structure Theory (RST) [
Warrant nucleus Instance Situation satellite Instance* Situation nucleus satellite* interactant*
Span relation Instance Relation statement Instance Statement
relation Relation
Antithesis
Background identifier Symbol Circumstance
Concession … statement
Statement
Interaction interactant Instance* Warrant
Substantiation
Rebuttal type Symbol Backing
Undercut
… The reasoning model defines a mapping between RST and the Toulmin model. This makes it possible to represent argumentative reasoning using RST discourse structures. As shown in Fig. 1, the elements of the model are warrants, spans, statements, relations, and interactions. A warrant establishes a set of links between a nucleus and zero or more satellites. The nucleus and its satellites are represented as spans. A span consists of a CNL statement, and in the case of satellites, the satellite’s RST relation to its nucleus. In argumentative terms, the nucleus corresponds to a claim, and the satellites corespond to grounds. Each satellite (or ground) links to the nucleus (or claim) by means of a rhetorical relation. That said, it should be noted that while some rhetorical relations are clearly argumentative, or at least inferential, others are merely synthetic, and the reasoning model must take this into account. Examples of inferential relations include Condition, Evidence, Means, Otherwise, and the causal relations. Examples of synthetic relations include Background, Circumstance, Elaboration, Restatement, and Summary. In a synthetic relation, the satellite and nucleus are logically conjunctive, but the nucleus is more salient than the satellite. This distinction between synthetic and inferential relations supports application of the reasoning process, facilitating both explanatory and argumentative discourse.
Interactions define the rules for synthesizing complex structures to create an explanation network. An interaction occurs when a nucleus, satellite, or warrant of one structure can be unified with a nucleus, satellite, or warrant of another structure. Interactions are defined in terms of the possible relationships between warrants, satellites, and nuclei. For example, if the claim of one argument unifies with the ground of another, a substantiation interaction is said to occur. Fig. 2 shows examples of substantiation and concomitance, and Table 1 defines the full set of interactions.
Substantiation
Concomitance
With this reasoning model it is possible to represent highly expressive explanation
networks that may be queried at varying levels of depth. In natural language
processing, Marcu [
Generating Discourse Structures
For the value of these discourse structures to be realized, it will be necessary to
provide an efficient means for their generation. Although parsing discourse relations
in CNL may be less difficult than natural language, it is not a trivial problem. The
difficulties lie not merely in the complexities of the language, but in the subtleties of
the RST relation definitions themselves. Consider for example the distinction between
Antithesis and Concession. Antithesis prescribes that the writer has positive regard for
the nucleus and that the satellite and nucleus are mutually incompatible, e.g. “Rather
than waste time teaching at the university, Charles pursued a lucrative career in the
publishing industry.” The Concession relation, on the other hand, prescribes that the
writer has positive regard for the nucleus but that there is not necessarily an
incompatibility between it and the satellite, e.g. “Although his mother would have
preferred that he teach, Charles pursued a lucrative career in the publishing industry.”
Following these definitions it might seem that any instance of the Antithesis relation
could also be coded as Concession [
For CNL, the answer, it seems to us, is that DBR structures would be created the
same way as other CNL discourse structures—namely they would be created as part
of the authoring process. For example, Attempto Controlled English supports several
discourse representation structures for representing composite sentences, such as
conditions, coordinates, and subordinates [
An administrator can not verify every system, but it is necessary that if a system is a compromised system then the administrator must verify it.
Although it is possible that an administrator believes that a system is up-to-date, it is not provable that the system is invulnerable.
Interaction Substantiation. The claim of one argument is used as the ground of another Rebuttal. The claims of two arguments are incompatible Backing. An argument substantiates the warrant of another Undercut. The claim of one argument is incompatible with the ground of another Dissociation. The claim of one argument disputes the warrant of another Convergence. Two arguments lead to the same claim, with possible accrual Concomitance. Two arguments use the same ground to establish distinct claims Confusion. The grounds of two arguments are incompatible
Definition substantiation(arg(G1,C1,W1) & arg(C1,C2,W2)) rebuttal(arg(G1,C1,W1) & arg(G2,C2,W2)) &
incompatible(C1,C2)) backing(arg(G1,C1,W1) & arg(G2,C2,C1)) undercut(arg(G1,C1,W1) & arg(G2,C2,W2) &
incompatible(C1,G2)) dissociation(arg(G1,C1,W1) & arg(G2,C2,W2) &
incompatible(C1,W2)) accrual(arg(G1,C1,W1) & arg(G2,C1,W2)) concomitance(arg(G1,C1,W1) & arg(G1,C2,W2)) confusion(arg(G1,C1,W1) & arg(G2,C2,W2) &
incompatible(G1, G2))
In addition, we may be able to build on this through recognition of syntactically
recognizable rhetorical forms, such as sorites, hypothetical syllogism, and dilemma.
Paragraph breaks and punctuation cues could also be used to support recognition of
larger composite structures [
This paper has defined an approach to representing and reasoning about complex composite structures in controlled natural languages. This is accomplished through definition of a reasoning model that synthesizes rhetorical structure theory with Toulmin’s argumentative model and Perelman’s theory of argument strategy. By defining rules for managing interactions among inferential and synthetic structures, DBR provides the basis for representing, summarizing, and interacting with explanatory and argumentative discourse, and it expands the scope of problems that may be addressed using controlled natural languages. Some anticipated future work includes identification of an experimental RST relation set for CNL, developing a prototype for encoding composite texts, and further definition of the reasoning model.