Thanks for sharing your work. As a hobby, I have spent years working on extracting semantic ontologies from natural language, so it was fun to see someone else's take on the problem.
As other have mentioned, you will make progress more efficiently if you survey the linguistics literature, where a tremendous number of very smart people have spent decades grappling with the same essential problems.
Heterodox linguistics is a veritable goldmine of ideas that can be implemented in AI. My favorite approach is Richard Hudson's "word grammar," which you can read about here: http://www.phon.ucl.ac.uk/home/dick/wg.htm
Word grammar is particularly well suited for coding, because it strips away lots of arbitrary linguistic formalisms in favor of a flexible, network-centric framework. Some of the core principles, like default inheritance, were actually taken directly from computer science.
Comments
Thanks for sharing your work. As a hobby, I have spent years working on extracting semantic ontologies from natural language, so it was fun to see someone else's take on the problem.
As other have mentioned, you will make progress more efficiently if you survey the linguistics literature, where a tremendous number of very smart people have spent decades grappling with the same essential problems.
Heterodox linguistics is a veritable goldmine of ideas that can be implemented in AI. My favorite approach is Richard Hudson's "word grammar," which you can read about here: http://www.phon.ucl.ac.uk/home/dick/wg.htm
Word grammar is particularly well suited for coding, because it strips away lots of arbitrary linguistic formalisms in favor of a flexible, network-centric framework. Some of the core principles, like default inheritance, were actually taken directly from computer science.