Meaning–text theory

Meaning–text theory (MTT) is a theoretical linguistic framework, first put forward in Moscow by Aleksandr Žolkovskij and Igor Mel’čuk, for the construction of models of natural language. The theory provides a large and elaborate basis for linguistic description and, due to its formal character, lends itself particularly well to computer applications, including machine translation, phraseology, and lexicography. General overviews of the theory can be found in Mel’čuk (1981) and (1988).

Linguistic models in MTT operate on the principle that language consists in a mapping from the content or meaning (semantics) of an utterance to its form or text (phonetics). Intermediate between these poles are additional levels of representation at the syntactic and morphological levels.

Representations at the different levels are mapped, in sequence, from the unordered network of the semantic representation (SemR) through the dependency tree-structures of the Syntactic Representation (SyntR) to a linearized chain of morphemes of the Morphological Representation (MorphR) and, ultimately, the temporally-ordered string of phones of the Phonetic Representation (PhonR) (not generally addressed in work in this theory). The relationships between representations on the different levels are considered to be translations or mappings, rather than transformations, and are mediated by sets of rules, called "components", which ensure the appropriate, language-specific transitions between levels.

Semantic representations (SemR) in meaning–text theory consist primarily of a web-like semantic structure (SemS) which combines with other semantic-level structures (most notably the Semantic-Communicative Structure [SemCommS], which represents what is commonly referred to as "Information Structure" in other frameworks). The SemS itself consists of a network of predications, represented as nodes with arrows running from predicate nodes to argument node(s). Arguments can be shared by multiple predicates, and predicates can themselves be arguments of other predicates. Nodes generally correspond to lexical and grammatical meanings as these are directly expressed by items in the lexicon or by inflectional means, but the theory allows the option of decomposing meanings into more fine-grained representation via processes of semantic paraphrasing, which are also key to dealing with synonymy and translation-equivalencies between languages. SemRs are mapped onto the next level of representation, the Deep-Syntactic Representation, by the rules of the Semantic Component, which allow for a one to many relationship between levels (that is, one SemR can potentially be expressed by a variety of syntactic structures, depending on lexical choice, the complexity of the SemR, etc.). The structural description and the (semi-) automatic generation of SemR are subject to research. Here the decomposition takes advantage of the Semantic Primes of the Natural Semantic Metalanguage to determine a termination criterion of the decomposition.

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