Dialectic Reasoning with Inconsistent Information
  From an inconsistent database non-trivial arguments may be constructed both
for a proposition, and for the contrary of that proposition. Therefore,
inconsistency in a logical database causes uncertainty about which conclusions
to accept. This kind of uncertainty is called logical uncertainty. We define a
concept of "acceptability", which induces a means for differentiating
arguments. The more acceptable an argument, the more confident we are in it. A
specific interest is to use the acceptability classes to assign linguistic
qualifiers to propositions, such that the qualifier assigned to a propositions
reflects its logical uncertainty. A more general interest is to understand how
classes of acceptability can be defined for arguments constructed from an
inconsistent database, and how this notion of acceptability can be devised to
reflect different criteria. Whilst concentrating on the aspects of assigning
linguistic qualifiers to propositions, we also indicate the more general
significance of the notion of acceptability.
