Expert-built lexical resources are known to provide information of good quality for the cost of low coverage. This property limits their applicability in modern NLP applications. Building descriptions of lexical-semantic relations manually in sufficient volume requires a huge amount of qualified human labour. However, given some initial version of a taxonomy is already built, automatic or semi-automatic taxonomy enrichment systems can greatly reduce the required efforts. We propose and experiment with two approaches to taxonomy enrichment, one utilizing information from word definitions and another from word usages, and also a combination of them. The first method retrieves co-hyponyms for the target word from distributional semantic models (word2vec) or language models (XLM-R), then looks for hypernyms of co-hyponyms in the taxonomy. The second method tries to extract hypernyms directly from Wiktionary definitions. The proposed methods were evaluated on the Dialogue-2020 shared task on taxonomy enrichment. We found that predicting hypernyms of cohyponyms achieves better results in this task. The combination of both methods improves results further and is among 3 best-performing systems for verbs. An important part of the work is detailed qualitative and error analysis of the proposed methods, which provide interesting observations of their behaviour and ideas for the future work.
В общем случае клеточная схема из функциональных и коммутационных элементов (КСФКЭ) представляет собой математическую модель интегральных схем (ИС), которая учитывает особенности их физического синтеза. Принципиальным отличием этой модели от хорошо изученных классов схем из функциональных элементов (СФЭ) является наличие дополнительных требований на геометрию схемы, которые обеспечивают учет необходимых трассировочных ресурсов при создании ИС. Предметом изучения многих авторов стала сложность реализации мультиплексорной функции алгебры логики (ФАЛ) в различных классах схем. В настоящей работе устанавливаются асимптотически точные верхние и нижние оценки площади КСФКЭ, реализующей мультиплексорную ФАЛ порядка $n$. Конструктивно построено семейство схемных мультиплексоров порядка $n$ с площадью, равной верхней оценке, и предложен метод получения соответствующей нижней оценки.
The cellular schema model (CS) was first proposed in 1967 by S.S. Kravtsov, who also obtained the order of the Shannon function for it. Model CS is a mathematical model of integrated circuits (IC), taking into account features of physical synthesis. Presence of requirements for geometry schemes that ensure that the necessary routing resources are taken into account when creation of IP, represents a fundamental difference from good studied classes of circuits from functional elements (SFE). Similar mathematical model in foreign sources was described in 1980 K.D. Thompson. For IP-related studies, the model is fundamental, and is considered a satisfactory approximation for IS, at least for single crystal systems. Moreover, she remains an accurate approximation for small areas (individual components) IP in cases where the model cannot correctly reflect all features of the designed systems. In this work asymptotic estimates for the area of cellular schemes are established, implementing a decoder of order n with repeated inputs.
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