Integration of World Knowledge for Natural Language Understanding
This book concerns non-linguistic knowledge required to perform computational natural language understanding (NLU). The main objective of the book is to show that inference-based NLU has the potential for practical large scale applications.First, an intro
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Atlantis Thinking Machines Series Editor: Kai-Uwe K¨uhnberger Institute of Cognitive Science University of Osnabr¨uck, Germany (ISSN: 1877-3273)
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Integration of World Knowledge for Natural Language Understanding Ekaterina Ovchinnikova USC ISI 4676 Admiralty Way Marina del Rey, CA 90292 USA
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Atlantis Thinking Machines Volume 1: Enaction, Embodiment, Evolutionary Robotics. Simulation Models for a Post-Cognitivist Science of Mind - Marieke Rohde, Ezequiel A. Di Paolo Volume 2: Real-World Reasoning: Toward Scalable, Uncertain Spatiotemporal, Contextual and Causal Inference - Ben Goertzel, Nil Geisweiller, L´ucio Coelho, Predrag Janiˇci´c, Cassio Pennachin
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978-94-91216-52-7 978-94-91216-53-4 1877-3273
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Foreword
Inference-based natural language understanding (NLU) was a thriving area of research in the 1970s and 1980s. It resulted in good theoretical work and in interesting small-scale systems. But in the early 1990s it foundered on three difficulties: • Parsers were not accurate enough to produce predicate-argument relations reliably, so that inference had no place to start. • Inference processes were not efficient enough nor accurate enough. • There was no large knowledge base designed for NLU applications. The first of these difficulties has been overcome by progress in statistical parsing. The second problem is one that many people, including Ekaterina Ovchinnikova, are working on now. The research described in this volume addresses the third difficulty, and indeed shows considerable promise in overcoming it. For this reason, I believe Dr. Ovchinnikova’s work has a real potential to reignite interest in inference-based NLU in the computational linguistics community. A key notion in her work is that there already exists sufficient world knowledge in a variety of resou
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