Nº 6 (2024)

The paper explores the distribution of various adjectival predicates (short form adjectives, long form adjectives in the nominative or instrumental case and passive participles) in Russian finite and non-finite clauses. Two factors turn out to determine the availability of adjectival predicates: (i) the type of the subject (overt DP vs. A-trace vs. PRO) and (ii) the case feature of the subject (nominative vs. other cases). Crucially, adjectival predicates differ as to the licensing factors: short form adjectives require that their subject (overt DP, A-trace or PRO) be nominative whereas nominative long form adjectives are only licit if their subject is a nominative overt DP or an A-trace of a nominative DP, but not a (nominative) PRO. Including adjectival passive into this picture gives rise to further discrepancies: the long form of the passive participle cannot form a passive predicate of a finite clause but is licit as such a predicate in non-finite clauses. The paper provides a formal analysis of the distribution of adjectival predicates, which relies on the following assumptions: (i) the categorial contrast of short and long forms; (ii) the syntactically represented opposition of control and raising; and (iii) PRO’s ability to receive the case feature via case assignment by complementizer or case transmission from the controller.

Karelian dialectal speech has been studied by linguists of Finnic languages in Russia and elsewhere for a century and a half, but such issues in Karelian dialectology as the fuzzy distribution of dialectal units over the territory, selection of the fundamental principle for dialectal division, determination of the language status of specific varieties, etc., have so far remained unresolved. This article summarizes the results of a study of Karelian dialectal speech based on archival materials from the 1930s–1970s in the “Dialectological Atlas of Karelian” (1997) performed using the dialectometric method of cluster analysis: the main contrastive phenomena of phonological, morphonological, morphological and lexical linguistic levels are listed, the distribution ranges are described and a typology of their members is provided, the current three-level dialect classification and the periodization of the history of the Karelian language are presented. Three supra-dialects are outlined on the dialect map: Karelian Proper, Livvi, and Ludic. They are distinguished on the basis of isoglosses of the morphological and morphonological systems inherited from the early period in the development of the language. The Karelian Proper supra-dialect rests upon Balto-Finnic Protolanguage and pan-Karelian novel traits; Livvi shows Balto-Finnic archaisms, features coming from the Old Veps substrate, which has affected different language levels, Old Karelian innovations, and its own dialectal features; Ludic incorporates Old Karelian innovations and a pronounced Old Veps substrate. The Karelian Proper supra-dialect was subdivided into three dialects: northern, southern (variants spoken in Central Russia), and a transitional dialect occupying an intermediate position between supra-dialects. Ludic is differentiated into two dialects: the original Ludic and the Pryazha dialect (Ludic variants spoken in the Pryazha District of Karelia), which was heavily influenced in later periods by neighboring Livvi sub-dialects. Variants of the Livvi supra-dialect proved to be relatively uniform. The making of the dialects was shaped by late Old Karelian dialectal differences and intensive contacts in the border areas of the supra-dialects, whereas the twenty sub-dialectal groups became differentiated through relatively recent phonetic and lexical innovations and contact influence of the neighboring languages.

The study aims to establish whether language models trained on unlabeled text data can parametrize agreement variation. We compared the acceptability judgments made by native speakers and the probability metrics predicted by the language model ruBERT without fine-tuning. As a specific linguistic phenomenon, we considered predicate agreement with a coordinated subject in Russian. We analyzed in detail which syntactic, morphological, and semantic factors influenced sentence acceptability and probability. The experimental data enables us to reveal the role of each factor and their interaction. Besides the standard logarithmic probability, we considered sentence length and unigram probability. We assumed that the model would assign the highest probability to the most acceptable agreement strategy. However, our hypothesis was not confirmed: the correlation between probability and acceptability is lower for sentences with agreement variation than for sentences without variation. The linear position — the subject-predicate order and the conjuncts’ order — turned out to be the only factor which equally influences the acceptability and probability of a sentence. If the gender features of conjuncts match, the acceptability of singular agreement increases while the probability does not change. The animacy of conjuncts and the predicate symmetry influence neither acceptability nor probability. Our research demonstrates that ruBERT cannot be used to parametrize predicate agreement with a coordinated subject. The acceptability of a sentence is based on subtle linguistic contrasts which are not significant for the computer evaluation of its probability.