UzbekLexLacuna: A Sense-Level Dataset for Modeling Uzbek–English Cross-Linguistic Lexical, Cultural, Semantic, and Pragmatic Lacunae

Abstract

In cross-lingual natural language processing (NLP) systems, expressing a meaning from one language through an appropriate lexical unit in another language is an important task. However, many semantically and culturally rich Uzbek concepts, including kinship terms, ceremonial vocabulary, forms of address, and expressions related to traditional medicine, do not have direct and concise equivalents in English. In this work, we present UzbekLexLacuna, an Uzbek–English dataset developed to represent such cases at the sense level. The dataset is designed for the systematic description of lexical, cultural, semantic, and pragmatic lacunae. The cleaned release candidate contains 760 TRUE_LACUNA entries and 100 NOT_LACUNA polysemy-control entries, yielding a total of 860 curated sense-level records with predefined benchmark splits. All entries were constructed through a systematic analysis of Uzbek–English equivalence based on the five-volume Explanatory Dictionary of the Uzbek Language. The annotation scheme distinguishes the scope of a lacuna (FULL or PARTIAL) from its source (CULTURAL, SEMANTIC, or PRAGMATIC). This structure supports sense-level lacuna detection and classification, the development of translation strategies, and the creation and evaluation of multi-task NLP models. The dataset is released under the CC BY 4.0 license together with controlled vocabularies, provenance metadata, and benchmark splits.