The main task that this thesis deals with is the provision of a comprehensive
analysis covering a meaningful subset of English and developing a computational
implementation that is able to show understanding of this language subset, in part
via limited visualisation.There is a well accepted analogy that says that eventualities exist in time, in ways
that are similar to how objects exist in space. This analogy is used as a framework
to investigate in detail those activities that are the eventuality analogue of plural
and mass objects—multiple instances of an activity, or continuous occurrence of
an activity respectively. These are called extended activities.We examine the ways in which natural language is used to describe these kinds
of activities, and discuss ways in which the meanings of such language can be
represented. We concentrate on language that is in the form of instructions, and
discuss the special relationship between instructions and activities.Using the idea that some of our understanding of language comes from the context within which the language is being understood, we identify those parts of
language about extended activities that are independent of context and indicate
the places where context would play a part. Focusing on the context-independent
part, the development of a grammar that can be used in an understanding system
demonstrates that it is feasible to interpret important aspects of such language
computationally. Further, the system includes a semi-graphical visualisation component that depicts in space the internal structure of the extended activity in
time.The work in this thesis relies on the notion that language about extended activities
is playing a role analogous to that of object quantification. That is, instead of the
more common view that such language is playing the role of event modification, we
take the view that it plays the role of event quantification. This notion has been
introduced by Moltmann, and taking this approach allows the identification and
representation of meanings that would otherwise be omitted. Further, incorporating this into the computational framework is feasible, and an established approach
to object quantification is used to implement event quantification
