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Question Answering in the Context of Causal Mechanisma

Abstract

model of human question answering (called QUEST) accounts for the answers that adults produce when they answer different categories of open-class questions (such as why, how, when, what-enabled, and what-are-the-consequences). This project investigated the answers that adults generate when events are queried in the context of biological, technological, and physical mechanisms. According to QUEST, an event sequence in a scientific mechanism is represented as a causal network of events and states; a teleological goal hierarchy may also be superimposed on the causal network in biological and technological domains, but not in physical systems (e.g., rainfall, earthquake). When questions are answered, QUEST systematically operates on the causal networks and goal hierarchies that underlie a causal mechanism. Answers to how and enablement questions sample causal antecedents of the queried event in the causal network; consequence questions sample causal consequents. Answers to when questions sample antecedents to a greater extent than consequents even though events from both directions fumish sensible answers. Answers to why questions sample both causal antecedents in the causal network and superordinate goals from goal hierarchies that exist in technological and biological knowledge structures.

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