WHAT IS ARGUMENT TEXT GENERATION ?

Argument texts written by humans are appropriately structured to express
judgments and attitudes on topics based on the standpoint of the author.

By computer, however, it is difficult to produce coherent texts. Therefore,
it is necessary to consider coherence and appropriate structure planning if
high quality argument texts are to be generated by computer. The goal of
our research is to investigate the argument strategy for text coherence and
clear standpoint expression.

GENERATION MECHANISM

We set the standpoint of the system by assigning it an argument goal.
Dulcinea puts forward an argument that justifies the given argument goal
according to its beliefs. The argument texts consist of direct grounds for
the argument goal, refutations for the expected opposing arguments, together
with examples. The beliefs consist of three types of belief contents: Fact,
Rule, and Judgment. An example of beliefs is given below.


  Rules:      change[obj2=bus-route,loc=L]decrease[obj2=passenger,loc=L].
  Facts:      introduce[obj=one-way-system,loc=Midosuji].
  Judgments:  ng[abolish[obj=bus]].

The argument goals we give the system can be of one of the three kinds of
modal expressions listed in the table below, where A stands for some state
of affairs. If a judgment g(A) exists in the system's belief, then the system
believes A to be good.




Dulcinea represents the semantic contents of an argument as an argument
graph. The following figure shows an argument graph that insists on the
argument goal "the two-way lane must be introduced". A two-way lane is a
lane that allows buses to drive the "wrong way" up a one-way street.

Then, the argument strategy on the linguistic text structure is applied to
the argument graph to organize abstract text structure FTS(Functional Text
Structure), which represents not only the semantic contents, but also the text
structure.


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