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Referring expression generation (REG) is the subtask of natural language generation (NLG) that received most scholarly attention. While NLG is concerned with the conversion of non-linguistic information into natural language, REG focuses only on the creation of referring expressions (noun phrases) that identify specific entities called targets .
Definite referring expressions refer to an identifiable individual or class (The Dalai Lama; The Coldstream Guards; the student with the highest marks), whilst indefinite referring expressions allow latitude in identifying the referent (a corrupt Member of Parliament; a cat with black ears—where a is to be interpreted as 'any' or 'some actual ...
Since the phrase "some dog is annoying" is not a referring expression, according to Russell's theory, it need not refer to a mysterious non-existent entity. Furthermore, the law of excluded middle need not be violated (i.e. it remains a law), because "some dog is annoying" comes out true: there is a thing that is both a dog and annoying.
A context model (or context modeling) defines how context data are structured and maintained (It plays a key role in supporting efficient context management). [1] It aims to produce a formal or semi-formal description of the context information that is present in a context-aware system. In other words, the context is the surrounding element for ...
The theory classifies nominals according to two features, [±anaphor] and [±pronominal], which are binary. The binding characteristics of a nominal are determined by the values of these features, either plus or minus. Thus, a nominal that is [-anaphor, -pronominal] is an R-expression (referring expression), such as a common noun or a proper name.
In Noam Chomsky's government and binding theory in linguistics, an R-expression (short for "referring expression" (the linked article explains the different, broader usage in other theories of linguistics) or "referential expression") is a noun phrase that refers to a specific real or imaginary entity.
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Modeling and simulation (M&S) is the use of models (e.g., physical, mathematical, behavioral, or logical representation of a system, entity, phenomenon, or process) as a basis for simulations to develop data utilized for managerial or technical decision making.