On 26/04/2011 11:08 AM, John F. Sowa wrote:
>>>> And what the effect is on legacy software and databases i.e. not
>>>> losing or recreating data, instead bringing them up to speed for
>>>> more precise information sharing and requirements tracking.
>>> The absence of any such explanation -- or even any mention of such
>>> issues -- is the reason why mainstream IT ignores the Semantic Web.
>> It may explain the lack of enthusiasm on the part of some in this forum
>> about the inclusion of Ontology in the Watson project.
>> I am not sure whether it is based on some deep understanding of Watson
>> that makes them believe that the role of ontologies in the Watson
>> reasoning process is really non-essential and could be removed without
>> impacting the effectiveness of the overall system or is it because
>> ontology is not the user-facing technology.
>> The applications of the technology used in Watson will likely create the
>> biggest demand for ontologists who can assist developers to build the
>> key ontologies in the particular domain.
> Some people involved in the Watson project, such as Chris Welty,
> certainly knew OWL and RDF. And the project manager, David Ferrucci,
> had earned a PhD in AI.
> The project used ontology, but their major database was DB2 -- a good,
> old fashioned relational DB. For complex reasoning, they used Prolog.
> See the article (abstract below) about using Prolog to reason with
> information expressed in UIMA, which was another project by Ferrucci.
Perhaps this is an example of a typical enterprise's use of ontology.
A fraction of the total solution but key to driving the understanding of
the application domain's entire knowledge base. (01)
> I believe that using Prolog and avoiding OWL is an important step
> forward in integrating semantic systems with mainstream IT.
> Source: http://arxiv.org/abs/0809.0680v1
> The Prolog Interface to the Unstructured Information Management Architecture
> Paul Fodor, Adam Lally, David Ferrucci
> In this paper we describe the design and implementation of the Prolog
> interface to the Unstructured Information Management Architecture (UIMA)
> and some of its applications in natural language processing. The UIMA
> Prolog interface translates unstructured data and the UIMA Common
> Analysis Structure (CAS) into a Prolog knowledge base, over which, the
> developers write rules and use resolution theorem proving to search and
> generate new annotations over the unstructured data. These rules can
> explore all the previous UIMA annotations (such as, the syntactic
> structure, parsing statistics) and external Prolog knowledge bases (such
> as, Prolog WordNet and Extended WordNet) to implement a variety of tasks
> for the natural language analysis. We also describe applications of this
> logic programming interface in question analysis (such as, focus
> detection, answer-type and other constraints detection), shallow parsing
> (such as, relations in the syntactic structure), and answer selection.
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