Hi Opencog community!

So I recently discovered an interest in AGI and have started to research
various things. In my wanderings I came across Opencog and it's amazing.
The conceptual Idea of atomspace is very powerful in its fundamental and
flexible nature.

While I'm interested in AGI/ML, I have more of a systems background with
some programming experience. My current understanding of ML is about on
the level of "I know flour and water go into the process of making bread,
I'm sure baking is part of the process, but I have no idea of all the
ingredients and processes involved". I do understand the difference between
Symbolic and Neural Nets. I've been reading the wiki and starting to soak
up all the concepts I can. While the wiki is great there are some topics
that seem like they may no longer apply.

I usually like to expand into new areas by picking some pet project and
working on it in milestones to grow my understanding. I thought a good
project might be a question and answer application on a knowledgebase.  In
trying to consider how it might be done in atomspace, I came across Lojban
topics and then later the paper about symbolic natural language grammar
induction (https://arxiv.org/abs/2005.12533). I didn't find more
information in the wiki and I wondered if there had been further
developments in the area that might be applicable.

My pet project would be like:
1) feed in text corpus
2) some process to parse text into atomspace
3) ability to query atomspace in natural language.
4) receive a natural language text answer.

Is this a doable task with opencog in its current state, or herculean for a
newcomer?

What are some milestones and topics/resources I may need to investigate
further work towards this pet project if it's doable? I'm currently working
through the opencog hands on sections to get a feel for things.

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