Tag Archives: link-grammar

Symbolic and Neural Nets: Two Sides of the Same Coin

Deep learning and neural nets are all the rage, today, and have displaced symbolic AI systems in most applications. It’s commonly believed that the two approaches have nothing to do with each other; that they’re just completely different, and that’s … Continue reading

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Why Hypergraphs?

I’ve recently been hacking on creating a new parser for the Link Grammar theory of natural language parsing. I want to couple parsing to machine learning (ML), to that I can use ML to learn natural languages. To do that, I need to place everything in a certain abstract data representation framework that allows graph rewrite rules, logical reasoning, and Bayesian probabilistic reasoning to be combined. This framework exists in OpenCog, but few people know or understand this. That this framework also has a firm foundation in model theory, category theory (even n-categories!) and type theory is even less well known. To explain all this, I just wrote a simple, easy introduction to all of these ideas, and how they come together. Follow the link for more. Continue reading

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The Viterbi Parser

The new Viterbi decoder for Link Grammar should offer better integration with higher level semantic algorithms! Continue reading

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Frequency of grammatical disjuncts

The link-grammar parser uses labeled links to connect together pairs of words.  In order to capture the idea of proper grammatical construction, any given word is only allowed to have very specific links to its right or left: for example, … Continue reading

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proto-chatbot at last!

A prototype chatbot demonstrates the OpenCog NLP pipeline by parsing simple statements and answering simple questions. Continue reading

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