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Posts Tagged ‘NLP’

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.

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 [...]

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 [...]

‘believed by many’

A Linguist user recently had a question about part of a sentence that boiled down to something like the following: It is believed by many. The question was whether “many” was an adjective, cardinality, or noun in this sentence.  It’s a reasonable question!

Parsing Winograd Challenges

The Winograd Challenge is an alternative to the Turing Test for assessing artificial intelligence.  The essence of the test involves resolving pronouns.  To date, systems have not fared well on the test for several reasons.  There are 3 that come to mind: The natural language processing involved in the word problems is beyond the state [...]

TA/NLP: It’s a jungle out there!

Text analytics and natural language processing have made tremendous advances in the last few years.  Unfortunately, there is a lot more to understanding natural language that TA/NLP. I was reading a paper today about NLP pipelines for question answering that used machine learning to find what tools are good at what tasks and to configure [...]

Combinatorial ambiguity? No problem!

Working on translating some legal documentations (sales and use tax laws and regulations) into compliance logic, we came across the following sentence (and many more that are even worse): Any transfer of title or possession, exchange, or barter, conditional or otherwise, in any manner or by any means whatsoever, of tangible personal property for a [...]