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The verb 'rise' can be used both with property-denoting nouns like 'temperature' but also with NPs like 'a Titan' or 'China'. Whereas in the former case the change triggered by a rising event is directly related to the subject (its current value increases), this does not hold for 'a titan' or 'China'. In this case it is a property of these objects, say their height or their political power, which increases in value. Furthermore, 'rise' does not target a particular property as the examples above show. This data has led Cooper (2010) to the conclusion that it is presumably not possible (i) "to extract a single general meaning of words which covers all the particular meanings of the word in context", and (ii) "to determine once and for all the set of particular contextually determined meanings of a word". In this article we present a solution to the two problems raised by 'rise' in a frame theory. 'Rise' is analyzed as a scalar verb which does not lexicalize a complete scale in its meaning. Rather, it shows underspecification relative to the dimension (property) parameter of a scale. The set of admissible properties is determined by a constraint on the value ranges of properties. If the property is not uniquely determined by the subject, the comprehender uses probabilistic reasoning based on world knowledge and discourse information to defeasibly infer the most likely candidates from this set (2nd problem). The first problem is solved not by simply introducing objects into the representation of a discourse but instead by pairs consisting of an object and an associated frame component which collects the object information contributed by the discourse. Changes triggered by events like the one denoted by 'rise' are modelled as update operations on the frame component while the object component is left unchanged.

The verb 'rise' can be used both with property-denoting nouns like 'temperature' but also with NPs like 'a Titan' or 'China'. Whereas in the former case the change triggered by a rising event is directly related to the subject (its current value increases), this does not hold for 'a titan' or 'China'. In this case it is a property of these objects, say their height or their political power, which increases in value. Furthermore, 'rise' does not target a particular property as the examples above show. This data has led Cooper (2010) to the conclusion that it is presumably not possible (i) "to extract a single general meaning of words which covers all the particular meanings of the word in context", and (ii) "to determine once and for all the set of particular contextually determined meanings of a word". In this article we present a solution to the two problems raised by 'rise' in a frame theory. 'Rise' is analyzed as a scalar verb which does not lexicalize a complete scale in its meaning. Rather, it shows underspecification relative to the dimension (property) parameter of a scale. The set of admissible properties is determined by a constraint on the value ranges of properties. If the property is not uniquely determined by the subject, the comprehender uses probabilistic reasoning based on world knowledge and discourse information to defeasibly infer the most likely candidates from this set (2nd problem). The first problem is solved not by simply introducing objects into the representation of a discourse but instead by pairs consisting of an object and an associated frame component which collects the object information contributed by the discourse. Changes triggered by events like the one denoted by 'rise' are modelled as update operations on the frame component while the object component is left unchanged.