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Generating training data for word sense disambiguation in Russian© 2020 ABBYY PRODUCTION LLC. All rights reserved. The best approaches in Word Sense Disambiguation
All-words Word Sense Disambiguation for Russian Using Automatically Generated Text Collection annotated data is a big challenge for the word sense disambiguation task. As a solution to this problem, we
Erratum: All-words Word Sense Disambiguation for Russian Using Automatically Generated Text Collection (Cybernetics and Information Technologies 20:4 (90-107) DOI: 10.2478/cait-2020-0049)This note concerns the word order of the authors names and correction of a printing error. 1
Context-Based Rules for Grammatical Disambiguation in the Tatar Language of the disambiguation process. Grammatical ambiguity is widely represented in agglutinative languages like Turkic
Neural Network Recognition of Russian Noun and Adjective Cases in the Google Books Ngram Corpus and adjective cases in the Google Books Ngram corpus. The recognition was performed by using information on word
Natural Language Processing Based on Semantic Patterns Approach attention is paid to word
collocations on the level of meaning and word sense
disambiguation
Methods and software tools of morphological disambiguation in the texts in tatar morphology and the fixed order of the words, the accuracy reaches 94-96%. And for the Russian language
Модификация метода разрешения лексической многозначности в области биомедициныРазрешение лексической многозначности (Word Sense Disambiguation) является промежуточной задачей
в
Natural Language and Computational Linguistics at the University of SussexIn this project we develop new ways of estimating the frequency distributions of the senses
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