Learn how to implement and apply a full NLP stack for deep cognitive analysis of language. This talk will take you through the development of an integrated deep NLP system for question answering using a combination of existing open source tools and technologies. I will tell you how to extend and specialize these tools for new domains, and show the development tools and best practices for extension. I will provide performance metrics and where multi-strategy approaches can yield additional leverage. I'll show how you can both use and contribute to the open source development project.

You'll learn about:

• Use of the Stanford NLP tools for POS tagging, parsing, coreference, NER, dependency parsing. How to tune these approaches, and how to apply them as a front end for deep language understanding
• How to employ formal linguistics to generate logical interpretations of language
• How to use formal ontology as a representation of linguistic semantics
• How to employ theorem proving in linguistic question answering
• How to generate language from logic