If this conversation continues, it should reflect a proper spelling of "relations" in the title, apologies for that error.
Gary Berg-Cross, Ph.D.
NSF INTEROP Project
SOCoP Executive Secretary Knowledge Strategies Potomac, MD
240-426-0770 On Fri, Aug 9, 2013 at 11:17 AM, Gary Berg-Cross <gbergcross@xxxxxxxxx> wrote:
Pat C
My reference to case relations as molecules was not meant to be so literal and instead gestured back to my earlier post on the models being useful for certain things but just approximations.
So case relations might do well as a formalized theory for some discourse analysis, but we may find more fundamental, semantic relations as part of cognitive development. Early child interactions with the world may lead to ideas a personal theory/mental model of CAUSE and CHANGE. These might provide some basis for the idea AGENT. The idea of the use of a mental model like this might provide a grander, formalized model that bridges theories of child cognitive and linguistic development.
It would be more flexible and might explain how we can construct something that approximates a case relation which in terms becomes a linguistic tool for humans, but the forms these take may vary a bit over individuals and culture and thus is not itself a final theory.
Gary Berg-Cross, Ph.D.
NSF INTEROP Project
SOCoP Executive Secretary Knowledge Strategies Potomac, MD
On Thu, Aug 8, 2013 at 11:30 PM, Patrick Cassidy <pat@xxxxxxxxx> wrote:
Gary,
On two points: [GB-C]
> He provided a highlight of work, but in that list I didn't see Fillmore's Case grammar,
which did have an important role in other part's of John's postings such as the
Verb Semantics Ontology project. This might not provide ultimate primitives, but are
perhaps molecules of a deeper chemistry.
I have been tempted to refer to primitive concepts as “atoms” that build up “molecules” of meaning, but there are important differences that make the analogy misleading. Many “primitive” concepts that are types within a hierarchy will be distinguished not by necessary and sufficient conditions (a logical “definition”), but only by necessary conditions. This leaves a lot of potential instances unspecified, and differs from the fixed properties of atoms; I believe that is indeed the way people use the primitives – they are only as specific as necessary for particular communication tasks. Perhaps even in the ‘atom’ analogy there can be some flexibility, since the isotopes of elements can have differing properties, but even that variability is much less than one sees with many conceptual primitives.
[GB-C]
> Case relations may not be the final word, but they provide a
starting point for core meta-relations that can be used to develop canonical propositions.
Yes, case relations are among the relations I believe are primitive, but they are still only a small part of the total number of primitive relations.
As my earlier note suggested, these hypotheses (however well motivated) need careful experimental testing to warrant strong assent, but the current trends in funding of NL research suggest that proper testing is still years in the future.
Pat
Patrick Cassidy
MICRA Inc. cassidy@xxxxxxxxx
1-908-561-3416
The Context and Inter-annotator agreement topic seems to have wound down, but along the
path of that discussion there was this idea of semantic primitives. John Sowa provied an historical list of people who have addressed this seductively, common sense
idea of selecting a small number of primitives for defining everything. It is, as he noted:
" one of the oldest in the history of philosophy, logic, linguistics, and AI. It can be traced back at least to 500 BC
with Pythagoras, Plato, and Aristotle. " He provided a highlight of work, but in that list I didn't see Fillmore's Case grammar,
which did have an important role in other part's of John's postings such as the
Verb Semantics Ontology project. This might not provide ultimate primitives, but are
perhaps molecules of a deeper chemistry. Case relations may not be the final word, but they provide a
starting point for core meta-relations that can be used to develop canonical propositions.
As John noted, more research is needed but this is one tool that can be used for now.
SOCoP Executive Secretary On Sun, Aug 4, 2013 at 1:28 PM, John F Sowa <sowa@xxxxxxxxxxx> wrote:
Pat,
PC > The point at issue is whether all of the senses of a particular word
> needed for language understanding can be included in a semantic lexicon.
> My experience suggests that they can, even though new senses are being
> developed all the time. The new senses can also be included in the lexicon,
> if they are important enough to warrant the effort.
That claim is vague enough to cover all bases. If you want a project
that includes all word senses anyone considers important, I suggest
Wiktionary. It has "3,476,017 entries with English definitions from
over 500 languages":
http://en.wiktionary.org/wiki/Wiktionary:Main_Page
Large numbers of people around are actively updating and extending
Wiktionary. When the number of senses is in the millions and growing,
it seems hard to claim that there is any finite upper limit.
PC > JFS seems to be saying that failure of some groups to achieve a goal means
> that no amount of effort trying a related but different way can succeed More precisely, the idea of selecting a small number of primitives for
defining everything is one of the oldest in the history of philosophy,
logic, linguistics, and AI. It can be traced back at least to 500 BC
with Pythagoras, Plato, and Aristotle. For summaries and references,
see http://www.jfsowa.com/talks/kdptut.pdf .
Slides 13 to 18: Aristotle's categories, definitions, and the Tree
of Porphyry for organizing them graphically.
Slides 91 to 93: Universal language schemes in the 17th and 18th
centuries. John Wilkins developed the largest and most impressive
set of primitives (40 genera subdivided in 2030 species). Wilkins
got help from other members to define 15,000 words in those terms.
For more information about these and other schemes, see references
by Knowlson (1975), Eco (1995), and Okrent (2009).
Slides 94 to 97: Ramon Llull's Great Art (Ars Magna), which included
Aristotle's categories, the Tree of Porphyry, rotating circles
for combining categories, and a methodology for using them to
answer questions. Leibniz was inspired by Llull to encode the
primitive categories in prime numbers and use multiplication
to combine them and division to analyze them.
Slide 98: Leibniz's method generated a lattice. For modern
lattice methods, see FCA and Ranganathan's facet classification.
Click on the URLs to see FCA lattices that are automatically
derived from WordNet and from Roget's Thesaurus.
Slides 99 to 101: Categories by Kant and Peirce. A suggested
updated version of Wilkins' hierarchy that includes more
modern developments.
Slides 102 to 107: Issues about the possibility of ever having
a complete, consistent, and finished ontology of everything.
For modern computational linguistics, the idea of selecting a set
of primitives for defining everything was proposed and implemented
in the late 1950s and early '60s:
1961 International Conf. on Machine Translation. See the table
of contents: http://www.mt-archive.info/NPL-1961-TOC.htm .
At that conference, Margaret Masterman proposed a list of 100
primitive concepts, which she used as the basis for lattices
that combine them in all possible ways. Yorick Wilks worked
with Masterman and others at CLRU, and he continued to use
her list of primitives for his later work in NLP. For the
list, see http://www.mt-archive.info/NPL-1961-Masterman.pdf
TINLAP (three conferences on Theoretical Issues in Natural Language
Processing from 1975 to 1987). The question of primitives was
the focus of these conferences. Yorick Wilks was one of the
organizers. Roger Schank (who also had a set of primitives for
defining action verbs) was prominent in them. For summaries,
see http://www.aclweb.org/anthology-new/T/T78/T78-1000.pdf
and http://www.aclweb.org/anthology-new/T/T87/T87-1001.pdf .
Anna Wierzbicka spent many years working on issues of selecting and
using a proposed set of primitives for defining words in multiple
languages. From Wikipedia: "She is especially known for Natural
Semantic Metalanguage, particularly the concept of semantic primes.
This is a research agenda resembling Leibniz's original "alphabet
of human thought", which Wierzbicka credits her colleague, linguist
Andrzej Bogusławski, with reviving in the late 1960s." Many people
tried to use her "semantic primes" in computational linguistics,
but none of those projects were successful.
I never said "No amount of effort trying a related but different way
can succeed." In fact, I have been proposing and *using* related
methods, but I always insist on keeping all options open.
There is no evidence that a fixed set exists, and an overwhelming
amount of evidence that Zipf's Law holds: there is an extremely long
tail to the distribution of word senses. But if you keep your options
open and *if* a fixed set of primitives is sufficient, then you will
discover that set. That is my recommended strategy.
> So the statistical approach has become vastly more funded than
> the ontological/analytical.
I certainly agree with you that a deeper analysis with ontologies and
related lexical resources is essential for NL understanding. I believe
that statistical methods are useful as a *supplement* to the deeper
methods. At VivoMind Research, we use *both*, but the emphasis is
on a syntactic and semantic analysis by symbolic methods.
> the current strong emphasis on the statistical approach is, I believe
> retarding progress by failing to develop even the most basic resources
> needed for the analytical stage 2 function.
I wholeheartedly agree. But from a selfish point of view, that gives
us a competitive advantage. We got a contract with the US Dept. of
Energy based on a competition with a dozen groups that used their
favorite methods of NLP.
For the test, all competitors were asked to extract certain kinds of
data from a set of research reports and present the results in a table.
The scores were determined by the number of correct answers. Our score
was 96%. The next best was 73%. Third best was above 50%, and all the
rest were below 50%.
For analyzing the documents, we used very general lexical resources
and a fairly simple general ontology. But we supplemented it with
a detailed ontology that was specialized for chemical compounds,
chemical formulas, and the related details of interest.
For an example of a spreadsheet with the results, see slides 49 & 50
of http://www.jfsowa.com/talks/relating.pdf .
John
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