RUSSE2018: a Shared Task on Word Sense Induction for the Russian Language
The paper describes the results of the first shared task on word sense induction (WSI) for the Russian language. While similar shared tasks were conducted in the past for some Romance and Germanic languages, we explore the performance of sense induction and disambiguation methods for a Slavic language that shares many features with other Slavic languages, such as rich morphology and virtually free word order. The participants were asked to group contexts of a given word in accordance with its senses that were not provided beforehand. For instance, given a word “bank” and a set of contexts for this word, e.g. “bank is a financial institution that accepts deposits” and “river bank is a slope beside a body of water”, a participant was asked to cluster such contexts in the unknown in advance number of clusters corresponding to, in this case, the “company” and the “area” senses of the word “bank”. For the purpose of this evaluation campaign, we developed three new evaluation datasets based on sense inventories that have different sense granularity. The contexts in these datasets were sampled from texts of Wikipedia, the academic corpus of Russian, and an explanatory dictionary of Russian. Overall, 18 teams participated in the competition submitting 383 models. Multiple teams managed to substantially outperform competitive state-of-the-art baselines from the previous years based on sense embeddings.
These proceedings include papers on subjects from a wide number of areas including theoretical linguistics, translation, computational linguistics, natural language processing, and applied linguistics, focusing on a variety of languages, ranging from familiar Indo-European languages to Mandarin Chinese, Wolof, and Dene Sųɬiné. In order to make the papers available to the wider research community, these proceedings are being published electronically and distributed freely at http://www.meaningtext.net
The article is implemented within the cognitive approach and is dedicated to the formation of a substantive core of the polysemantic verb, particularly of the verb of relations in the modern English. The first part of the article presents points of view on the semantic nature - "content plan" - of the word. In the second part of the paper the authors identify the main cognitive mechanisms underlying the formation of meanings of the verb compose, as well as its substantial core that combines all the lexical-semantic variants of a this verb.
The collected papers contain articles by famous and young scientists on actual problems of philology (cognitive linguistics, lexical semantics, semiotics, pragmatics, text linguistics, stylistics; poetics, literary criticism; translation, intercultural communication). The issue also presents research on foreign language teaching methods. The edition is addressed to linguists, translators, teachers, postgraduates, students and a wide readership.
Reading utilises at least two neural pathways. The temporal lexical route visually maps whole words to their lexical entries, whilst the nonlexical route decodes words phonologically via parietal cortex. Readers typically employ the lexical route for familiar words, but poor comprehension plus precocity at mechanically 'sounding out' words suggests that differences might exist in autism. Combined MEG/EEG recordings of adults with autistic spectrum conditions (ASC) and controls while reading revealed preferential recruitment of temporal areas in controls and additional parietal recruitment in ASC. Furthermore, a lack of differences between semantic word categories was consistent with previous suggestion that people with ASC may lack a 'default' lexical-semantic processing mode. These results are discussed with reference to dual-route models of reading.
The paper continues research into words denoting everyday life objects in the Russian language. This research is conducted for developing a new encyclopedic thesaurus of Russian everyday life terminology. Working on this project brings up linguistic material which leads to discovering new trends and phenomena not covered by the existing dictionaries. We discuss derivation models which gain polularity: clipped forms (komp < komp’juter ‘computer’, nout < noutbuk ‘notebook computer’, vel < velosiped ‘bicycle’, mot<motocikl ‘motorbike’), competing masculine and feminine con- tracted nouns derived from adjectival noun phrases (mobil’nik (m.) / mo- bilka (f.) < mobil’nyj telefon (m.) ‘mobile phone’, zarjadnik (m.) / zarjadka (f.) < zarjadnoe ustrojstvo (n.) ‘AC charger’), hybrid compounds (plat’e- sviter ‘sweater dress’, jubka-brjuki ‘skirt pants’, shapkosharf ‘scarf hat’, vilkolozhka ‘spork, foon’). These words vary in spelling and syntactic behav- iour. We describe a newly formed series of words denoted multifunctional objects: mfushkaZ< MFU < mnogofunkcional’noe ustrojstvo ‘MFD, multi- function device’, mul’titul ‘multitool’, centr ‘unit, set’. Explaining the need to compose frequency lists of word meanings rather than just words, we of- fer a technique for gathering such lists and provide a sample produced from our own data. We also analyze existing dictionaries and perform various experiments to study the changes in word meanings and their comparative importance for speakers. We believe that, apart from the practical usage for our lexicographic project, our results might prove interesting for research in the evolution of the Russian lexical system.
In this paper we consider choice problems under the assumption that the preferences of the decision maker are expressed in the form of a parametric partial weak order without assuming the existence of any value function. We investigate both the sensitivity (stability) of each non-dominated solution with respect to the changes of parameters of this order, and the sensitivity of the set of non-dominated solutions as a whole to similar changes. We show that this type of sensitivity analysis can be performed by employing techniques of linear programming.
I give the explicit formula for the (set-theoretical) system of Resultants of m+1 homogeneous polynomials in n+1 variables