A while back, I took the WordNet database
and parsed it into a relational database so that I could access it with
VB. My purpose was to use it a
dictionary resource for chatterbots.
Then I found it could be used for other interesting things that a
conventional paper dictionary cannot do very well. For example, �what are the types of
citrus fruit?�
Grouping words according to synonym sets
(synsets) seems an effective means of organization, in that synsets are linked
to more specific and more general sets.
The synsets also include a brief definition or gloss. This type of organization gets around
the problem of a word having multiple meanings; it�s just listed in multiple
synsets. I include a couple examples of hypernym chains WordNet can produce as
a postscript.
It occurred to me that WordNet could be
used as an ontology in which various types of information could be stored and
accessed. Things as varied as
concepts or individuals have a place.
My hunch was that when data are organized and accessible, they could be
used for a range of purposes.
Another issue I have considered is how
best to handle meta-data about data such as poems, books, images, and so
on. At EllaZ Systems we refer to
these types of data as Convuns (conversational units). Convuns tend to have a lot of
properties in common, such as creator, date, type, summary, etc. When a conversation is about the Moon,
for example, a number of different Convuns and types of Convuns may make
appropriate fuel for conversation and interaction.
In taking a closer look at NARS, it seems
it could be used in a way similar to WordNet for categorizing words, concepts,
and instances of information. Of
course, NARS has the ability to do much more than merely categorize and store
information.
It should be straightforward to move the
70,000 or so synsets in WordNet into a NARS system. Perhaps this could serve as an initial
�grounding� of a new NARS entity.
For instances of information, Project Gutenberg contains thousands of
public domain texts, many photos are available from public sources, and so
on. Perhaps meta-data (in the
form of NARS statements) about Convuns could ground them enough that a NARS
(or other system) could think about them and look for patterns and
understanding. Meta-data
certainly helps me understand and enjoy information more!
Accessible, organized information would
be useful to both humans and emerging AI. It�s easy to envision NARS being a big
improvement over other cataloging methods, while being a part of AI
development. There is certainly
an appeal to the merging of data and intelligence, where the two become
one.
Kevin Copple
P.S. A couple hypernym chains of �pony�
are:
Sense 1 (pony) A range horse of the
western United States.
. . . is a type of: horse, Equus
caballus
. . . is a type of: equine, equid
. . . is a type of: odd-toed ungulate, perissodactyl,
perissodactyl mammal
. . . is a type of: ungulate, hoofed
mammal
. . . is a type of: placental, placental mammal,
eutherian, eutherian mammal
. . . is a type of: mammal
. . . is a type of: vertebrate,
craniate
. . . is a type of: chordate
. . . is a type of: animal, animate being, beast, brute,
creature, fauna
. . . is a type of: life form, organism, being, living
thing
. . . is a type of: entity, something
For another sense of �pony� in another
synset:
Sense 3 (pony, trot, crib) A literal
translation used in studying a foreign language (often used
illicitly).
. . . is a type of: translation, interlingual rendition,
rendering, version
. . . is a type of: written record, written
account
. . . is a type of: record
. . . is a type of: evidence
. . . is a type of: indication
. . . is a type of: signal, signaling,
sign
. . . is a type of: communication
. . . is a type of: social relation
. . . is a type of: relation
. . . is a type of: abstraction
