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Semantics is the study of meaning in communication. The word derives from Greek σημαντικός (semantikous), "significant",[1] from σημαίνω (semaino), "to signify, to indicate" and that from σήμα (sema), "sign, mark, token".[2] In linguistics it is the study of interpretation of signs as used by agents or communities within particular circumstances and contexts.[3] It has related meanings in several other fields.
Semanticists differ on what constitutes meaning in an expression. For example, in the sentence, "John loves a bagel", the word bagel may refer to the object itself, which is its literal meaning or denotation, but it may also refer to many other figurative associations, such as how it meets John's hunger, etc., which may be its connotation. Traditionally, the formal semantic view restricts semantics to its literal meaning, and relegates all figurative associations to pragmatics, but many find this distinction difficult to defend.[4] The degree to which a theorist subscribes to the literal-figurative distinction decreases as one moves from the formal semantic, semiotic, pragmatic, to the cognitive semantic traditions.
The word semantic in its modern sense is considered to have first appeared in French as sémantique in Michel Bréal's 1897 book, Essai de sémantique'. In International Scientific Vocabulary semantics is also called semasiology. The discipline of Semantics is distinct from Alfred Korzybski's General Semantics, which is a system for looking at non-immediate, or abstract meanings.
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In linguistics, semantics is the subfield that is devoted to the study of meaning, as inherent at the levels of words, phrases, sentences, and even larger units of discourse (referred to as texts). The basic area of study is the meaning of signs, and the study of relations between different linguistic units: homonymy, synonymy, antonymy, polysemy, paronyms, hypernymy, hyponymy, meronymy, metonymy, holonymy, exocentricity / endocentricity, linguistic compounds. A key concern is how meaning attaches to larger chunks of text, possibly as a result of the composition from smaller units of meaning. Traditionally, semantics has included the study of connotative sense and denotative reference, truth conditions, argument structure, thematic roles, discourse analysis, and the linkage of all of these to syntax.
Formal semanticists are concerned with the modeling of meaning in terms of the semantics of logic. Thus the sentence John loves a bagel above can be broken down into its constituents (signs), of which the unit loves may serve as both syntactic and semantic head.
In the late 1960s, Richard Montague proposed a system for defining semantic entries in the lexicon in terms of lambda calculus. Thus, the syntactic parse of the sentence above would now indicate loves as the head, and its entry in the lexicon would point to the arguments as the agent, John, and the object, bagel, with a special role for the article "a" (which Montague called a quantifier). This resulted in the sentence being associated with the logical predicate loves (John, bagel), thus linking semantics to categorial grammar models of syntax. The logical predicate thus obtained would be elaborated further, e.g. using truth theory models, which ultimately relate meanings to a set of Tarskiian universals, which may lie outside the logic. The notion of such meaning atoms or primitives are basic to the language of thought hypothesis from the 70s.
Despite its elegance, Montague grammar was limited by the context-dependent variability in word sense, and led to several attempts at incorporating context, such as :
In the Chomskian tradition in linguistics there was no mechanism for the learning of semantic relations, and the nativist view considered all semantic notions as inborn. Thus, even novel concepts were proposed to have been dormant in some sense. This traditional view was also unable to address many issues such as metaphor or associative meanings, and semantic change, where meanings within a linguistic community change over time, and qualia or subjective experience. Another issue not addressed by the nativist model was how perceptual cues are combined in thought, e.g. in mental rotation.[5]
This traditional view of semantics, as an innate finite meaning inherent in a lexical unit that can be composed to generate meanings for larger chunks of discourse, is now being fiercely debated in the emerging domain of cognitive linguistics[6] and also in the non-Fodorian camp in Philosophy of Language.[7] The challenge is motivated by
A concrete example of the latter phenomenon is semantic underspecification — meanings are not complete without some elements of context. To take an example of a single word, "red", its meaning in a phrase such as red book is similar to many other usages, and can be viewed as compositional.[8] However, the colours implied in phrases such as "red wine" (very dark), and "red hair" (coppery), or "red soil", or "red skin" are very different. Indeed, these colours by themselves would not be called "red" by native speakers. These instances are contrastive, so "red wine" is so called only in comparison with the other kind of wine (which also is not "white" for the same reasons). This view goes back to de Saussure:
and may go back to earlier Indian views on language, especially the Nyaya view of words as indicators and not carriers of meaning.[10]
An attempt to defend a system based on propositional meaning for semantic underspecification can be found in the Generative Lexicon model of James Pustejovsky, who extends contextual operations (based on type shifting) into the lexicon. Thus meanings are generated on the fly based on finite context.
Another set of concepts related to fuzziness in semantics is based on prototypes. The work of Eleanor Rosch and George Lakoff in the 1970s led to a view that natural categories are not characterizable in terms of necessary and sufficient conditions, but are graded (fuzzy at their boundaries) and inconsistent as to the status of their constituent members.
Systems of categories are not objectively "out there" in the world but are rooted in people's experience. These categories evolve as learned concepts of the world — meaning is not an objective truth, but a subjective construct, learned from experience, and language arises out of the "grounding of our conceptual systems in shared embodiment and bodily experience".[4] A corollary of this is that the conceptual categories (i.e. the lexicon) will not be identical for different cultures, or indeed, for every individual in the same culture. This leads to another debate (see the Whorf-Sapir hypothesis or Eskimo words for snow).
English nouns are found by language analysis to have 25 different semantic features, each associated with its own pattern of fMRI brain activity. The individual contribution of each parameter predicts the fMRI pattern when nouns are considered thus supporting the view that nouns derive their meaning from prior experience linked to a common symbol.[11]
In computer science, where it is considered as an application of mathematical logic, semantics reflects the meaning of programs or functions.
In this regard, semantics permits programs to be separated into their syntactical part (grammatical structure) and their semantic part (meaning). For instance, the following statements use different syntaxes (languages), but result in the same semantic:
Generally these operations would all perform an arithmetical addition of 'y' to 'x' and store the result in a variable called 'x'.
Semantics for computer applications falls into three categories:[12]
The Semantic Web refers to the extension of the World Wide Web through the embedding of additional semantic metadata; s.a. Web Ontology Language (OWL).
In psychology, semantic memory is memory for meaning, in other words, the aspect of memory that preserves only the gist, the general significance, of remembered experience, while episodic memory is memory for the ephemeral details, the individual features, or the unique particulars of experience. Word meaning is measured by the company they keep; the relationships among words themselves in a semantic network. In a network created by people analyzing their understanding of the word (such as Wordnet) the links and decomposition structures of the network are few in number and kind; and include "part of", "kind of", and similar links. In automated ontologies the links are computed vectors without explicit meaning. Various automated technologies are being developed to compute the meaning of words: latent semantic indexing and support vector machines as well as natural language processing, neural networks and predicate calculus techniques.