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Lexical semantics (also known as lexicosemantics), as a subfield of linguistic semantics, is the study of word meanings. [ 1 ] [ 2 ] It includes the study of how words structure their meaning, how they act in grammar and compositionality , [ 1 ] and the relationships between the distinct senses and uses of a word.
The latter, semantic network theory, proposes the idea of spreading activation, which is a hypothetical mental process that takes place when one of the nodes in the semantic network is activated, and proposes three ways this is done: priming effects, neighborhood effects, and frequency effects, which have all been studied in depth over the years.
Before the 1950s, there was no discussion of a syntax–semantics interface in American linguistics, since neither syntax nor semantics was an active area of research. [17] This neglect was due in part to the influence of logical positivism and behaviorism in psychology, that viewed hypotheses about linguistic meaning as untestable.
This can be explained by models that do not assume a distinct level between the semantic and the phonological stages (and so lack a lemma representation). [3] During the process of language activation, lemma retrieval is the first step in lexical access. In this step, meaning and the syntactic elements of a lexical item are realized as the lemma.
Conceptual semantics is a framework for semantic analysis developed mainly by Ray Jackendoff in 1976. Its aim is to provide a characterization of the conceptual elements by which a person understands words and sentences, and thus to provide an explanatory semantic representation (title of a Jackendoff 1976 paper).
There are also elaborate types of semantic networks connected with corresponding sets of software tools used for lexical knowledge engineering, like the Semantic Network Processing System of Stuart C. Shapiro [41] or the MultiNet paradigm of Hermann Helbig, [42] especially suited for the semantic representation of natural language expressions ...
This representation can be used for tasks, such as those related to artificial intelligence or machine learning. Semantic decomposition is common in natural language processing applications. The basic idea of a semantic decomposition is taken from the learning skills of adult humans, where words are explained using other words.
These separate representations are postulated in order to explain the ways in which an expression's meaning can be partially independent of its pronunciation, e.g. scope ambiguities. LF is the cornerstone of the classic generative view of the syntax-semantics interface.