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Roles and anchors of semantic situations

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Abstract

Although neither theoretical nor computational linguists did provide sufficiently careful insight into the problem of semantic roles, recently some progress is being achieved in robotics (study of the simulation of human interaction), and mostly in multi-agent systems. Taking advantage of this motivation and applying it to the study of languages, I distinguish between various abstract ontological levels. Instead of using such concepts as <i>agentive</i>, <i>objective</i>, <i>experiencer</i>, etc., on the highest (generic) ontological level, I postulate generalised agents which are defined by the following ontological features, among others: (1) features of control (autonomy): <i>goal</i> and <i>feedback</i>, (2) features of emotion (character): <i>desire</i> and <i>intention</i>, (3) epistemic features (reason): <i>belief </i>and<i> cognition</i>, (4) communication features (language faculty): <i>verbal</i> and <i>visual</i>. In accordance with such ontological concepts, natural and artificial entities are obviously suited to fulfil the semantic roles of <i>agents</i> and <i>figures </i>respectively in the widest sense of these terms. I further propose to distinguish between three classes of generic ontological roles, namely active, median or passive. Here are examples of generic roles: (1) <i>active role</i> (Initiator, Causer, Enabler, Benefactor, Executor, Stimulant, Source, Instigator etc.), (2) <i>passive</i> <i>role</i> (Terminator, Affect, Enabled, Beneficient, Executed, Experiencer, Goal, etc.) and (3) <i>median</i> <i>role</i> (Mediator, Instrument, Benefit, Motor, Means etc.). Figures can play quasi-active (Q-active) roles.

References

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