TEXT B
A perennial problem in semantics is the delineation of its subject matter. The term meaning can be used in a variety of ways, and only some of these correspond to the usual understanding of the scope of linguistic or computational semantics. We shall take the scope of semantics to be restricted to the literal interpretations of sentences in a context, ignoring phenomena like irony, metaphor, or conversational implicature.
A standard assumption in computationally oriented semantics is that knowledge of the meaning of a sentence can be equated with knowledge of its truth conditions: that is, knowledge of what the world would be like if the sentence were true. This is not the same as knowing whether a sentence is true, which is usually an empirical matter, but knowledge of truth conditions is a prerequisite for such verification to be possible. Meaning as truth conditions needs to be generalized somewhat for the case of imperatives or questions, but 1s a common ground among all contemporary theories, in one form or another, and has an extensive philosophical justification.
A semantic description of a language is some finitely stated mechanism that allows us to say, for each sentence of the language, what its truth conditions are. Just as for grammatical description, a semantic theory will characterize complex and novel sentences on the basis of their constituents: their meanings, and the manner in which they are put together. The basic constituents will ultimately be the meanings of words and morphemes. The modes of combination of constituents are largely determined by the syntactic structure of the language. In general, to each syntactic rule combining some sequence of child constituents into a parent constituent, there will correspond some semantic operation combining the meanings of the children to produce the meaning of the parent.
A corollary of knowledge of the truth conditions of a sentence is knowledge of what inferences can be legitimately drawn from it. Valid inference is traditionally within the province of logic as is truth and mathematical logic has provided the basic tools for the development of semantic theories. One particular logical system, first order predicate calculus (FOPC), has played a special role in semantics as it has in many areas of computer science and artificial intelligence. FOPC can be seen as a small model of how to develop a rigorous semantic treatment for a language, in this case an artificial one developed for the unambiguous expression of some aspects of mathematics. The set of sentences or well formed formulae of FOPC are specified by a grammar, and a rule of semantic interpretation is associated with each syntactic construct permitted by this grammar. The interpretations of constituents are given by associating them with set-theoretic constructions from a set of basic elements in some universe of discourse. Thus for any of the infinitely large set of FOPC sentences we can give a precise description of its truth conditions, with respect to that universe of discourse. Furthermore, we can give a precise account of the set of valid inferences to be drawn from some sentence or set of sentences, given these truth conditions, or given a set of rules of inference for the logic.
Some natural language processing tasks (e.g., message routing, textual information retrieval, translation ) can be carried out quite well using statistical or pattern matching techniques that do not involve semantics in the sense assumed above. However, performance on some of these tasks improves if semantic processing is involved.
Some tasks, however, cannot be carried out at all without semantic processing of some form. One important example application is that of database query, of the type chosen for the Air Travel Information Service task. For example, if a user asks, "Does every flight from London to San Francisco stop over in Reykyavik" then the system needs to be able to deal with some simple semantic facts. Relational databases do not store propositions of the form every X has property P and so a logical inference from the meaning of the sentence is required. In this case, every X has property P is equivalent to there is no X that does not have property P and a system that knows this will also therefore know that the answer to the question is no if a non-stopping flight is found and yes otherwise.
Which of the following phenomena comes within the scope of semantics？（）
A. Irony.
B. Literal interpretations of sentences m a context.
C. Metaphor.
D. Conversational implicature.
