One of the things that I quickly discovered when first working on my "convert it all to Basic English" project is that the simplest words (prepositions and the simplest verbs in particular) are the biggest problem because they have so many different (though obscurely related) meanings (not to mention being part of one-off phrases).

Some of the problems are resolved by stronger typing (as in variable typing). For example, On-SituationLocalized is clearly meant to deal with two physical objects and shouldn't apply to neuroscience. But *that* sentence is easy after you realize that neuroscience really can only have the type of "field-of-study" or topic. The on becomes obvious then -- provided that you have that many variable types and rules for prepositions (not an easy thing).

And how would a young child or foreigner interpret on the Washington Monument or "shit list"? Both are physical objects and a book *could* be resting on them. It's just that there are more likely alternatives. On has a specific meaning (a-member-of-this-ordered-group) for lists and another specific meaning (about-this-topic) for books, movies, and other subject-matter-describers. The special on overrides the generic on -- provided that you have even more variable types and special rules for prepositions.

And "on fire" is a simple override phrase -- provided that you're keeping track of even more specific instances . . . .

- - - - -

Ben, your question is *very* disingenuous. There is a tremendous amount of domain/real-world knowledge that is absolutely required to parse your sentences. Do you have any better way of approaching the problem?

I've been putting a lot of thought and work into trying to build and maintain precedence of knowledge structures with respect to disambiguating (and overriding incorrect) parsing . . . . and don't believe that it's going to be possible without a severe amount of knwledge . . . .

What do you think?

----- Original Message ----- From: "Benjamin Goertzel" <[EMAIL PROTECTED]>
To: <[email protected]>
Sent: Wednesday, January 09, 2008 3:51 PM
Subject: Re: [agi] Incremental Fluid Construction Grammar released


What is the semantics of

   ?on-situation-localized-14 rdf:type texai:On-SituationLocalized

??

How would your system parse

"The book is on neuroscience"

or

"The book is on the Washington Monument"

or

"The book is on fire"

or

"The book is on my shit list"

???

thx
Ben

On Jan 9, 2008 3:37 PM, Stephen Reed <[EMAIL PROTECTED]> wrote:

Ben,

The use case utterance "the block is on the table" yields the following RDF statements (i.e. subject, predicate, object triples). A yet-to-be written discourse mechanism will resolve ?obj-4 to the known book and ?obj-18 to the
known table.

Parsed statements about "the book":
    ?obj-4 rdf:type cyc:BookCopy
     ?obj-4 rdf:type texai:FCGClauseSubject
     ?obj-4 rdf:type texai:PreviouslyIntroducedThingInThisDiscourse
    ?obj-4 texai:fcgDiscourseRole texai:external
    ?obj-4 texai:fcgStatus texai:ingleObject

Parsed statements about "the table":
     ?obj-18 rdf:type cyc:Table
    ?obj-18 rdf:type texai:PreviouslyIntroducedThingInThisDiscourse
    ?obj-18 texai:fcgDiscourseRole texai:external
     ?obj-18 texai:fcgStatus texai:SingleObject

Parsed statements about "the book on the table":
     ?on-situation-localized-14 rdf:type texai:On-SituationLocalized
    ?on-situation-localized-14 texai:aboveObject ?obj-4
    ?on-situation-localized-14 texai:belowObject ?obj-18

Parsed statements about that the book "is" on the table ( the fact that
?on-situation-localized-14 is a proper sub-situtation of
?situation-localized-10 should also be here):
    ?situation-localized-10 rdf:type cyc:Situation-Localized
     ?situation-localized-10 texai:situationHappeningOnDate cyc:Now
    ?situation-localized-10 cyc:situationConstituents  ?obj-4

Cyc parsing is based upon semantic translation templates, which are stitched
together with procedural code following the determination of constituent
structure by a plug-in parser such as the CMU link-grammar.  My method
differs in that: (1) I want to get the entire and precise semantics from the utterance. (2) FCG is reversible, the same construction rules not only parse
input text, but can be applied in reverse to re-create the original
utterance from its semantics. Cyc has a separate system for NL generation. (3) Cyc hand-codes their semantic translation templates and I have in mind building an expert English dialog system using minimal hand-coded Controlled English, for the purpose of interacting with a multitude of non-linguists to
extend its linguistic knowledge.

-Steve

Stephen L. Reed

Artificial Intelligence Researcher
http://texai.org/blog
http://texai.org
3008 Oak Crest Ave.
Austin, Texas, USA 78704
512.791.7860




----- Original Message ----
From: Benjamin Goertzel <[EMAIL PROTECTED]>
To: [email protected]
Sent: Wednesday, January 9, 2008 1:45:34 PM
Subject: Re: [agi] Incremental Fluid Construction Grammar released

 Steve,

The output of FCG seems very syntax-ish...

Do you have mechanisms in texai for mapping the output of FCG into
higher-level, more semantic-ish relationships like the ones use in
OpenCyc?

As you know better than me, within Cyc they have a large system of
rules for mapping the syntactic output of their parser into their
semantic representation.

The degree to which an AI system learns such mapping rules, versus has
them hand-encoded, is a very important issue, because in many ways
these rules are a subtler and harder problem than the rules of syntax.

-- Ben G

On Jan 9, 2008 2:21 PM, Stephen Reed <[EMAIL PROTECTED]> wrote:
>
> On the SourceForge project site, I just released the Java library for
> Incremental Fluid Construction Grammar.
>
> Fluid Construction Grammar is a natural language parsing and generation
> system developed by researchers at emergent-languages.org. The system
> features a production rule mechanism for both parsing and generation > using
a
> reversible grammar. This library extends FCG so that it operates
> incrementally, word by word, left to right in English. Furthermore, its
> construction rules are adapted from Double R Grammar. See this blog > post
for
> more information about Double R Grammar.
>
> Execution scripts for a parsing benchmark and for the unit test cases > are
> supplied in Linux and Windows versions.
>
> Next tasks are to integrate IFCG into the existing, but not yet > released, > dialog framework. The framework will heuristically guide the > application
of
> construction rules during parsing, and plan the application of rules
during
> generation. Furthermore the framework will incrementally prune > alternate
> interpretations during parsing by employing Walter Kintsch's
> Construction/Integration method for discourse comprehension.
>
>
>
>
>
> -Steve
>
> Stephen L. Reed
>
> Artificial Intelligence Researcher
> http://texai.org/blog
> http://texai.org
> 3008 Oak Crest Ave.
> Austin, Texas, USA 78704
> 512.791.7860
>
>
>  ________________________________
> Looking for last minute shopping deals? Find them fast with Yahoo!
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