SimRelUz: Similarity and Relatedness scores as a Semantic Evaluation dataset for Uzbek language
Domaine:
natural language processingType de record:
paperdataset
Créateur:
SalKurGóm
Hôte:
Semantic relatedness between words is one of the core concepts in natural language processing, thus making semantic evaluation an important task. In this paper, we present a semantic model evaluation dataset: SimRelUz - a collection of similarity and relatedness scores of word pairs for the low-resource Uzbek language. The dataset consists of more than a thousand pairs of words carefully selected based on their morphological features, occurrence frequency, semantic relation, as well as annotated by eleven native Uzbek speakers from different age groups and gender. We also paid attention to the problem of dealing with rare words and out-of-vocabulary words to thoroughly evaluate the robustness of semantic models. Final version, published in the proceedings of SIGUL workshop of LREC 2022
Similaires
African Wordnet as a tool to identify semantic relatedness and semantic similarityIntroducing two Vietnamese Datasets for Evaluating Semantic Models of (Dis-)Similarity and RelatednessA SEMI-SUPERVISED FRAMEWORK NAMED AUGSBERT-UZ FOR HIGH-PERFORMANCE SEMANTIC TEXTUAL SIMILARITY IN UZBEKCASS: A Comprehensive Arabic Semantic Similarity DatasetDeep Contextualized Pairwise Semantic Similarity for Arabic Language QuestionsMulti-SimLex: A Large-Scale Evaluation of Multilingual and Crosslingual Lexical Semantic Similarity