Phil, (01)
That's the ultimate goal of AI: (02)
> Tala is not a CNL, because its goal (and to some extent, current design)
> is to support unconstrained NL syntax and unconstrained semantics. (03)
But the goal of *supporting* unconstrained syntax and semantics,
does not require that the notation(s) used to support it need to be
unconstrained in the same way. (04)
For example, our VivoMind tools support unconstrained NL with conceptual
graphs. The syntax of CGIF (Conceptual Graph Interchange Format) is
tightly constrained by the ISO standard for Common Logic. The semantics
(the definitions of the labels on those graphs) is not constrained by
the CL standard. But there are various levels of constraints that can
be imposed on a CG or collection of CGs: (05)
1. The tightest constraint would be a fixed ontology that specifies
all the labels (or 'names' in CL terminology). This method would
be appropriate for *proscriptive* constraints that enforce explicit
design decisions for a particular project or industry standard. (06)
2. A looser constraint is to have a very underspecified upper-level
ontology and a family (e.g., a lattice) of microtheories that can
be adopted (or generated) for various contexts or applications. (07)
3. A very flexible approach, which we have found useful for analyzing
a wide range of NL documents: A small upper-level based on the KR
ontology (see http://www.jfsowa.com/ontology ), an open-ended
variety of lexical resources (e.g., WordNet, Roget's Thesaurus,
IBM-CSLI Verb Ontology, FrameNet, etc.), and learning methods for
deriving (automatically and/or semi-automatically) a specialized
ontology for each document or corpus of documents. (08)
4. Many disputes in AI are between people who are trying to enforce
a proscriptive ontology and those who are trying to interpret
documents for which the ontology is unknown. We need both kinds
of ontologies -- sometimes in different parts of the same project
(or even the same document). (09)
> Your slides give the following definition:
> CNL = A subset of a natural language that has a well-defined mapping
> to and from a computable form.
> Under this definition, Tala could be considered a CNL... (010)
I tried to make that definition as loose as I could without being
hopelessly vague. I consider CNLs to be similar to Wittgenstein's
games: give examples and say "These and anything similar are CNLs."
A restrictive definition would stifle innovation, not promote it. (011)
>> Why haven't these great ideas become the foundation for the Semantic
>> Web? Should they be considered? If not, why not? If so, how?
>
> Perhaps one answer to the first question is that Berners-Lee (1998)
> specifically disclaimed "A Semantic Web is not Artificial Intelligence". (012)
Yes, but... If you look at his DAML proposal (2000), he cites a wide
range of AI systems and researchers. The chief designer of RDF (Guha)
had been the associate director of Cyc. Guha and Pat Hayes specified
the LBase semantics for RDF that was compatible with Common Logic. (013)
Other AI researchers defined a more specialized semantics for OWL-DL,
but Pat insisted on a version similar to LBase for OWL Full. The
disputes were not between AI and non-AI methods. They were disputes
between different AI factions. (014)
I suspect that the primary reason for Tim's statement was political:
The non-AI members of the W3C had a bad impression of AI based on
many years of unfulfilled promises (hype) from the AI community. (015)
> Regarding how to develop these ideas going forward, my recommendation
> is that people work on developing systems according to the TalaMind
> approach. (016)
If, as I suggested, you adopt a loose definition of CNL, that could
include a large family of methods -- ranging from Ed Lowry's PROSE,
Fred & Bozena Thompson's ASK, the VivoMind methods outlined above,
to many other systems that have been developed in AI. (017)
For a recent paper that says more about CGs and related systems,
see http://www.jfsowa.com/pubs/eg2cg.pdf . (018)
John (019)
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