Is anybody still using Conceptual Dependency Theory? Roger Schank did some interesting work on language processing with Conceptual Dependency (CD) in the 1970s. He then moved somewhat out of the field, being in Education these days. There were some useful applications in natural language generation (BABEL), story generation (TAILSPIN) and other areas, often involving planning and episodes rather than individual sentences.

Has anybody else continued to use CD or variants thereof? I am not aware of any other projects that do, apart from Hovy's PAULINE which uses CD as representation for the story to generate.
Although this model played an important role in contributing  to our present understanding of NLP and NLU, it is no longer useful in production systems and currently no successful commercial product follows this approach. 

In CDT the goal was to design an AI system that could draw logical inferences from sentences. In this system the goal was to make the meaning independent of the words used in the input.  

CDT modeled sentences by using tokens such as: locations, time, real world actions and real world objects. However as computational power became more common and less expensive, interest diverted to statistical models which were now outperforming the previous rule based systems.  

The problem with rule based approaches such as CDT is that they require manual development of linguistic rules which can be costly and which usually don't generalize well to other languages.

On the other hand, statistical approaches use  human language resources (multilingual textual corpora) more efficiently. Rather than using a rule based approach, statistical models make soft probabilistic decisions based on attaching real weights to the features making up the input data. (Wikipedia NLP)

This efficient use of human language resources leads to a model that is more accurate and robust especially when given unfamiliar input or input that contains errors. Statistical models also generalise well to other languages.