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Posts under ‘Natural Language’

Simply Smarter Intelligent Agents

Deep learning can produce some impressive chatbots, but they are hardly intelligent.  In fact, they are precisely ignorant in that they do not think or know anything. More intelligent dialog with an artificially intelligent agent involves both knowledge and thinking.  In this article, we educate an intelligent agent that reasons to answer questions.

Problems with Probabilistic Parsing

We are using statistical techniques to increase the automation of logical and semantic disambiguation, but nothing is easy with natural language. Here is the Stanford Parser (the probabilistic context-free grammar version) applied to a couple of sentences.  There is nothing wrong with the Stanford Parser!  It’s state of the art and worthy of respect for [...]

Confessions of a production rule vendor (part 2)

Going on 5 years ago, I wrote part 1.  Now, finally, it’s time for the rest of the story.

Simply Logical English

This is not all that simple of an article, but it walks you through, from start to finish, how we get from English to logic. In particular, it shows how English sentences can be directly translated into formal logic for use with in automated reasoning with theorem provers, logic programs as simple as Prolog, and [...]

Natural Intelligence

Deep natural language understanding (NLU) is different than deep learning, as is deep reasoning.  Deep learning facilities deep NLP and will facilitate deeper reasoning, but it’s deep NLP for knowledge acquisition and question answering that seems most critical for general AI.  If that’s the case, we might call such general AI, “natural intelligence”. Deep learning [...]

Iterative Disambiguation

In a prior post we showed how extraordinarily ambiguous, long sentences can be precisely interpreted. Here we take a simpler look upon request. Let’s take a sentence that has more than 10 parses and configure the software to disambiguate among no more than 10. Once again, this is a trivial sentence to disambiguate in seconds [...]

“Only full page color ads can run on the back cover of the New York Times Magazine.”

A decade or so ago, we were debating how to educate Paul Allen’s artificial intelligence in a meeting at Vulcan headquarters in Seattle with researchers from IBM, Cycorp, SRI,  and other places. We were talking about how to “engineer knowledge” from textbooks into formal systems like Cyc or Vulcan’s SILK inference engine (which we were [...]

“I don’t own a TV set. I would watch it.”

The following excerpt is from Hobbs, Jerry R. “Toward a useful concept of causality for lexical semantics.” Journal of Semantics 22.2 (2005): 181-209.

Are vitamins subject to sales tax in California?

What is the part of speech of “subject” in the sentence: Are vitamins subject to sales tax in California? Related questions might include: Does California subject vitamins to sales tax? Does California sales tax apply to vitamins? Does California tax vitamins? Vitamins is the direct object of the verb in each of these sentences, so, [...]

Common sense about deep learning

I regularly build deep learning models for natural language processing and today I gave one a try that has been the leader in the Stanford Question Answering Dataset (SQuAD).  This one is a impressive NLP platform built using PyTorch.  But it’s still missing the big picture (i.e., it doesn’t “know” much). Generally,  NLP systems that [...]