Reasoning Usefully about Mental States During Discourse Understanding: A Metaphor Based Approach

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This Artificial Intelligence project investigates part of the problem of discerning the coherence relationships within natural language discourse. The relationships of interest are between discourse components that describe or presuppose mental states (propositional attitudes). The mental states can be those of the speaker, listener, or any person mentioned by the discourse, and can be states of belief, intention hope, desire, etc. The focus of this work is on descriptions that rely implicitly of explicity on commonsense models of the mind that people often deploy, such as the prevalent model of a mind and its beliefs as respectively a physical container and some physical objects within it. Commonsense models are frequently relied upon in mental-state descriptions and are important factors in discourse coherence relationships, yet previous detailed work on representing and reasoning about mental states has largely skirted the issues. This research relates strongly, however, to work by psychologists and linguists on metaphor and metonymy, because the commonsense models are metaphorical and metonymy is often involved as well. The project includes the development of a prototype AL discourse- interpretation system, as well as major data collection activities: collection of information about mental-state language through experiments with human subjects, and through semi-automated examination of diverse natural language texts, including definitions and examples in machine-readable dictionaries. Annotated compendia of examples from these texts will be produced. The project is also concered with the relationship between mental-state descriptions in English and those in other language, notably Spanish, with a view to contributing to machine-translation work at our laboratory.