Pursuing the Goal of Language Understanding

• Authors: Arun Majumdar;John Sowa;John Stewart
• Venue: ICCS '08 Proceedings of the 16th international conference on Conceptual Structures: Knowledge Visualization and Reasoning
• Year: 2008

No human being can understand every text or dialog in his or her native language, and no one should expect a computer to do so. However, people have a remarkable ability to learn and to extend their understanding without explicit training. Fundamental to human understanding is the ability to learn and use language in social interactions that Wittgenstein called language games. Those language games use and extend prelinguistic knowledge learned through perception, action, and social interactions. This article surveys the technology that has been developed for natural language processing and the successes and failures of various attempts. Although many useful applications have been implemented, the original goal of language understanding seems as remote as ever. Fundamental to understanding is the ability to recognize an utterance as a move in a social game and to respond in terms of a mental model of the game, the players, and the environment. Those models use and extend the prelinguistic models learned through perception, action, and social interactions. Secondary uses of language, such as reading a book, are derivative processes that elaborate and extend the mental models originally acquired by interacting with people and the environment. A computer system that relates language to virtual models might mimic some aspects of understanding, but full understanding requires the ability to learn and use new knowledge in social and sensory-motor interactions. These issues are illustrated with an analysis of some NLP systems and a recommended strategy for the future. None of the systems available today can understand language at the level of a child, but with a shift in strategy there is hope of designing more robust and usable systems in the future.