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Posts Tagged ‘ERG’

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, [...]

‘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!

Robust Inference and Slacker Semantics

In preparing for some natural language generation[1], I came across some work on natural logic[2][3] and reasoning by textual entailment[4] (RTE) by Richard Bergmair in his PhD at Cambridge: Monte Carlo Semantics: Robust Inference and Logical Pattern Processing with Natural Language Text The work he describes overlaps our approach to robust inference from the deep, [...]

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 [...]

Background for our Semantic Technology 2013 presentation

In the spring of 2012, Vulcan engaged Automata for a knowledge acquisition (KA) experiment.  This article provides background on the context of that experiment and what the results portend for artificial intelligence applications, especially in the areas of education.  Vulcan presented some of the award-winning work referenced here at an AI conference, including a demonstration [...]

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.