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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 .
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.
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 ...
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 ...
Verbal context influences the way an expression is understood; hence the norm of not citing people out of context. Since much contemporary linguistics takes texts, discourses, or conversations as the object of analysis, the modern study of verbal context takes place in terms of the analysis of discourse structures and their mutual relationships ...
A language model is a probabilistic model of a natural language. [1] In 1980, the first significant statistical language model was proposed, and during the decade IBM performed ‘Shannon-style’ experiments, in which potential sources for language modeling improvement were identified by observing and analyzing the performance of human subjects in predicting or correcting text.