I think that, for starters, importing the concept-net data into the
atomspace would be a good start.

This would be a multi-step process:
1) import it any-old-how
2) import it such that the format is compatible with the existing nlp
subsystem
3) build some rudimentary question-answering system (on that can only
answer 1 or 2 or 3 question types, from the imported data
4) see if you can do anything whizzy with PLN

I think I ordered this in terms of difficulty/complexity.  I think I would
be very interested in looking at, overseeing, advising steps 2,3...

--linas

On Wed, Feb 20, 2019 at 6:25 AM Johannes Castner <[email protected]> wrote:

> Hi everyone,
>
> I think I might want to try to improve on the solution below using opencog
> in some way.  In particular, maybe the solution could be improved by first
> inferring some connections between ideas that are not represented in
> ConceptNet, from the ConceptNet data -- things that are likely also true
> but that are not expressed and then doing the embeddings on the more
> complete graph.  Any thoughts?  How does one get to more metaphorical and
> less explicit knowledge?  I find this endlessly fascinating!
>
> http://blog.conceptnet.io/posts/2016/conceptnet-5-5-and-conceptnet-io/
>
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