THE MEANING Û TEXT THEORY: MULTISTAGE TRANSFORMER AND GOVERNMENT PATTERNS
The European linguists went their own way, sometimes pointing out some oversimplifications and inadequacies of the early Chomskian linguistics.
In late 1960´s, a new theory, the Meaning Û Text model of natural languages, was suggested in Russia. For more than 30 years, this theory has been developed by the scientific teams headed by I. Mel’čuk, in Russia and then in Canada, and by the team headed by Yu. Apresian in Russia, as well as by other researchers in various countries. In the framework of the Meaning Û Text Theory (MTT), deep and consistent descriptions of several languages of different families, Russian, French, English and German among them, were constructed and introduced to computational practice.
One very important feature of the MTT is considering the language as multistage, or multilevel, transformer of meaning to text and vice versa. The transformations are comprehended in a different way from the theory by Chomsky. Some inner representation corresponds to each level, and each representation is equivalent to representations of other levels. Namely, surface morphologic, deep morphologic, surface syntactic, deep syntactic, and semantic levels, as well as the corresponding representations, were introduced into the model.
The description of valencies for words of any part of speech and of correspondence between the semantic and syntactic valencies have found their adequate solution in this theory, in terms of the so-called government patterns.
The government patterns were introduced not only for verbs, but also for other parts of speech. For a verb, GP has the shape of a table of all its possible valency representations. The table is preceded by the formula of the semantic interpretation of the situation reflected by the verb with all its valencies. The table is succeeded by information of word order of the verb and its actants.
If to ignore complexities implied by Spanish pronominal clitics like me, te, se, nos, etc., the government pattern of the Spanish verb dar can be represented as
Person X gives thing Y to person Z
| X = 1 | Y = 2 | Z = 3 |
| 1.1 N | 2.1 N | 3.1 aN |
The symbols X, Y, and Z designate semantic valencies, while 1, 2, and 3 designate the syntactic valencies of the verb. Meaning ‘give’ in the semantic formula is considered just corresponding to the Spanish verb dar, since dar supposedly cannot be represented by the more simple semantic elements.
The upper line of the table settles correspondences between semantic and syntactic valencies. For this verb, the correspondence is quite simple, but it is not so in general case.
The lower part of the table enumerates all possible options of representation for each syntactic valency at the syntactic level. The options operate with part-of-speech labels (N for a noun, Vinf for a verb in infinitive, etc.) and prepositions connecting the verb with given valency fillers. In our simplistic example, only nouns can fill all three valencies, only the preposition a is used, and each valency have the unique representation. However, such options can be multiple for other verbs in Spanish and various other languages. For example, the English verb give has two possible syntactic options for the third valency: without preposition (John gives him a book)vs. with the preposition to (John gives a book to him).
The word order is generally not related with the numeration of the syntactic valencies in a government pattern. If all permutations of valencies of a specific verb are permitted in the language, then no information about word order is needed in this GP. Elsewhere, information about forbidden or permitted combinations is given explicitly, to make easier the syntactic analysis. For example, the English verb give permits only two word orders mentioned above.
Thus, government patterns are all-sufficient for language description and significantly differ from subcategorization frames introduced in the generative grammar mainstream.