People constantly talk to each other about experience or knowledge resulting from spatial perception; they describe the size, shape, orientation and position of objects using a wide range of spatial expressions. The semantic treatment of such expressions presents particular challenges for natural language processing. The meaning representation used must be capable of distinguishing between fine-grained sense differences and ambiguities grounded in our experience and perceptual structure. While there have been many different approaches to the representation and processing of spatial expressions, most computational characterizations have been restricted to particularly narrow problem domains. The chapters in this volume reflect a commitment to the development of cognitively informed computational treatments of spatial language and spatatial representation. Therefore, the chapters present computational work, empirical work, or a combination of both.

People constantly talk to each other about experience or knowledge resulting from spatial perception; they describe the size, shape, orientation and position of objects using a wide range of spatial expressions. The semantic treatment of such expressions presents particular challenges for natural language processing. The meaning representation used must be capable of distinguishing between fine-grained sense differences and ambiguities grounded in our experience and perceptual structure. While there have been many different approaches to the representation and processing of spatial expressions, most computational characterizations have been restricted to particularly narrow problem domains. The chapters in this volume reflect a commitment to the development of cognitively informed computational treatments of spatial language and spatatial representation. Therefore, the chapters present computational work, empirical work, or a combination of both.

People constantly talk to each other about experience or knowledge resulting from spatial perception; they describe the size, shape, orientation and position of objects using a wide range of spatial expressions. The semantic treatment of such expressions presents particular challenges for natural language processing. The meaning representation used must be capable of distinguishing between fine-grained sense differences and ambiguities grounded in our experience and perceptual structure. While there have been many different approaches to the representation and processing of spatial expressions, most computational characterizations have been restricted to particularly narrow problem domains. The chapters in this volume reflect a commitment to the development of cognitively informed computational treatments of spatial language and spatatial representation. Therefore, the chapters present computational work, empirical work, or a combination of both.