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Posts under ‘Ontology’

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.

Affiliate Transactions covered by The Federal Reserve Act (Regulation W)

Benjamin Grosof, co-founder of Coherent Knowledge Systems, is also involved with developing a standard ontology for the financial services industry (i.e., FIBO).  In the course of working on FIBO, he is developing a demonstration of defeasible logic concerning Regulation W of the The Federal Reserve Act.  Regulation W specifies which transactions involving banks and their [...]

Automatic Knowledge Graphs for Assessment Items and Learning Objects

As I mentioned in this post, we’re having fun layering questions and answers with explanations on top of electronic textbook content. The basic idea is to couple a graph structure of questions, answers, and explanations into the text using semantics.  The trick is to do that well and automatically enough that we can deliver effective [...]

Higher Education on a Flatter Earth

We’re collaborating on some educational work and came across this sentence in a textbook on finance and accounting: All of these are potentially good economic decisions. We use statistical NLP but assist with the ambiguities.  In doing this, we relate questions and answers and explanations to the text. We also extract the terminology and produce [...]

Knowledge acquisition using lexical and semantic ontology

In developing a compliance application based on the institutional review board policies of John Hopkins’ Dept. of Medicine, we have to clarify the following sentence: Projects involving drugs or medical devices other than the use of an approved drug or medical device in the course of medical practice and projects whose data will be submitted [...]


In preparation for generating RIF and SBVR from the Linguist, we have produced an OWL ontology for the pertinent aspects of the SBVR specification.  We hope that this is helpful to others and would sincerely appreciate any corrections or comments on how to improve it. Paul

NLP: depictive in an HPSG lexicon?

We’re having a great time using OWL to clarify and enrich the semantics of the rich model underlying the ERG. Here’s an example, FYI. If you’d like to know more (or help), please drop us a line! Overall the project will demonstrate our capabilities for transforming everyday sentences into RIF and business rule languages using SBVR extended with defeasibility and other capabilities, all modeled in the same OWL ontology.

Event-centric BPM and goal-driven processing

The slides for my Business Rules Forum presentation on event semantics and focusing on events in order to simplify process definition and to facilitate more robust governance and compliance are at Event-centric BPM. After the talk I spoke with Jan Verbeek and Gartjan Grijzen of Be Informed and reviewed their software, which is excellent.  They [...]

Simple problems with the semantic web

The standard for defining ontologies these days is OWL and Protege.  Unfortunately, OWL lacks any notion of exceptions in inheritance or any other notion of defeasibility. So, although you may want to say that birds fly, you’re ontology will be broken (or become much more complicated) when you realize there are birds that can’t fly, [...]

Tendencies and purpose matter

The basic formal ontology (BFO) offers a simple, elegant process model.   It adds alethic and teleological semantics to the more procedural models, among which I would include NIST’s process specification language (PSL) along with BPMN. Although alethic typically refers to necessary vs. possible, it clearly subsumes the probable or expected (albeit excluding deontics0).  For example, [...]