U niversal D ependencies Treebank for U zbek (2025)

Abstract: We present the first Universal Dependencies treebank for Uzbek, a low-resource language from the Turkic family. The treebank contains 500 sentences (5850 tokens) sourced from the news and fiction genres and it is annotated for lemmas, part-of-speech (POS) tags, morphological features, and dependency relations. We describe our methodology for building the treebank, which consists of a mix of manual and automatic annotation and discuss some constructions of the Uzbek language that pose challenges to the UD framework.

## introduction although uzbek ranks as the second turkic language in terms of speakers after turkish @xcite , computational resources for this language are scarce. we aim to partially fill this gap by introducing the first fully annotated universal dependencies (ud) treebank for uzbek -uzbek-ut (uzbek universal treebank) 1 . the ud framework facilitates consistent morpho-syntactic annotation across different languages @xcite and represents an open community initiative aimed at creating annotated corpora for numerous languages. as of v.2.15, ud includes 296 treebanks covering 168 languages foot_1 . nowadays treebanks are essential for the development of natural language processing (nlp) tools and are also increasingly used in linguistic research. the present paper is organized as follows. in section 2, we provide a brief sketch of the uzbek language and in section 3, we review the existing computational resources for uzbek. section 4 forms the core of the paper, describing the steps involved in the treebank development, including automatic annotation and manual correction. in section 5, we analyze some constructions that pose challenges to the ud framework. section 6 summarizes our work and proposes directions for future research. ## the uzbek language uzbek is a member of the karluk branch of the turkic language family and has the status of official language in uzbekistan. with over 40 million speakers, it is primarily used in uzbekistan and surrounding central asian countries, and considered as the second-most widely spoken turkic language after turkish @xcite . the official script of the language is latin, but the old cyrillic script is still in use @xcite . the treebank described in this work only contains uzbek sentences written in the latin script. uzbek grammar shares similarities with other turkic languages, but computational resources developed for cognate languages cannot be directly applied. from a typological perspective, uzbek is a null-subject, highly agglutinative language and lacks gender distinctions and articles. like other turkic languages, uzbek has a basic sov word order, which is quite flexible and can be easily altered for information structure by fronting the topic @xcite . its morphology is highly regular and the standard orthography does not indicate vowel harmony or consonant assimilation. modifiers precede the head noun and are generally follow the pronoun-quantifieradjective order. number agreement in the nominal phrase is not obligatory, and nouns modified by quantifiers are often unmarked for plural. @xcite o'zbekistonda yil boshidan beri soliq tushumlari qanday o'zgargani tahlil qilindi . propn noun noun adp noun noun pron verb noun verb punct uzbekistan.loc year start.poss.abl since tax revenue.pl.poss how change.part.3sg analysis make.pass.pst obl nmod obl case nmod nsubj advmod csubj compound root punct 'how tax revenues have changed in uzbekistan since the beginning of the year was analyzed.' figure 1: ud annotation of an uzbek sentence 3 related work early computational resources for uzbek included a morphological parser written in prolog (matlatipov and vetulani, 2009), which however lacked support for complex words. sharipov et al. (2022) introduced an expanded tagset through deeper morphological and syntactic analysis. this was followed by the creation of uzbektagger, a rulebased pos tagger @xcite , which was based on 12 pos tags and tested on the manually annotated data. the development of stemmers and lemmatizers @xcite has been another important contribution. uzmorphanalyzer, introduced by @xcite , represents a more comprehensive tool, integrating a stemmer, lemmatizer, and pos tagger. additionally, a robust finite-state transducer (fst)-based morphological analyzer, included in the apertium monolingual package, supports uzbek text processing foot_2 . significant efforts have also been directed toward dataset creation, including wordnet-type synsets @xcite , sentiment analysis datasets @xcite , semantic evaluation dataset @xcite ) and text classification datasets @xcite . however, there remains a lack of a fully annotated gold-standard dataset for training automatic taggers and parsers. in recent years, neural transformer-based language models like uzbert @xcite and bertbek @xcite have emerged. these models were pretrained and evaluated against multilingual bert @xcite , showing promising results in 4 treebank development ## challenging constructions in this section, we address some of the challenges we have encountered in building the ut treebank for different annotation fields: upos, universal features and syntactic relations. as for upos tagging, the particle + verb pattern used in verbal multi-word expressions (mwes) is particularly challenging, as the particle does not have a standalone meaning and does not occur outside of a verbal mwe. for example, tashkil in the mwe tashkil qil 'establish' does not belong to any pos in uzbek and the whole phrase is considered a verb in traditional uzbek grammar. however, ud requires to analyze this phrase as two tokens tagged part and verb, respectively. the main challenge is the lack of a comprehensive list of such mwes, requiring frequent dictionary lookups to verify if the first element of the verb phrase belongs to a different pos category. with regard to universal features, uzbek verbs can be morphologically marked for the voice category by more than one value. in such cases, the actual value is determined by the most external voice suffix. for instance, ko'ch-ir-il-ish-i 'relocate-cau-pass-vnoun-3sg' has a causative and a passive morpheme, but the verb is ultimately considered as having a passive voice. this ambiguity should be resolved manually, as the parser has no representation for the order of the morphemes. as for syntactic relations, postverbial constructions with auxiliary verbs, which are defined by @xcite as "converb[s] of a lexical verb and a second auxiliary verb form[ing] a verbal phrase with strong semantic fusion", are notoriously challenging to analyze. there are about 27 verbs in uzbek that can be used as auxiliaries to form such constructions, e.g. to'xtab 'stop' as in to'xtab qol ('lit.: stopping stay) 'end, finish' (see figure 2 ) @xcite . postverbial constructions are common in the turkic family, but their annotation lacks consistency across the ud treebanks for turkic languages. in the uyghur treebank, auxiliaries are analyzed as the head of an open clausal complement relation (xcomp) foot_9 , although this does not fully align with the ud guidelines. in the kyrgyz treebank, converbs are treated as the head of the relation, with the postverbial element assigned an auxiliary relation (aux) foot_10 . however, this seems inaccurate, as verbal features like person, tense and mood are marked on the postverbial element. in uzbek, words used as auxiliaries also have nonauxiliary uses, and aux is only assigned to modal and copular verbs. this inconsistency across languages highlights the need for a standardized approach. one potential solution is to introduce a new subtype for compound relations, pending discussion among turkic ud contributors and approval by the ud coordinators. in the meantime, we analyze such uzbek verb constructions with a compound relation, in which the postverbial element serves as the head. ## conclusion in this work, we presented the first ud treebank for uzbek -uzbek-ut. the annotation methodology was semi-automatic, starting from manual annotation of training data to automatic parsing with freely available tools, followed by human postediting. additionally, we analyzed constructions that are particularly challenging in the ud framework. despite its small size, the treebank serves as a quality resource for linguistic research and model training in several nlp tasks, which we intend to conduct in future work. in the future, this treebank can be extended in size, covering more registers and enriched with additional tags and improved solutions for mwes.