The paper describes VESUM, a large morphological dictionary of Ukrainian, as a valuable resource for the analysis and synthesis of Ukrainian morphological data. In line with its manifold practical uses, VESUM supplies a rich set of morphological features for more than 400,000 Ukrainian lemmas. Its lexical range extends beyond what is found in Ukrainian monolingual and grammatical dictionaries to cover proper names, abbreviations, alternative spellings, slang, deprecated items, dialectal and archaic words, etc. VESUM's inflectional paradigms include a number of substandard wordforms (marked as such) that occur in texts and need to be recognized by NLP applications. The paper describes VESUM's structure, morphological information it provides, its use in the LanguageTool language checker and in the Lucene search engine, as well as the dynamic tagging component that acts as a complement to the dictionary itself. VESUM's coverage of different text types is also discussed. The dictionary is provided as an open access source via an online repository for the NLP community and is made available online through a web interface in human-readable, searchable format. Morphological dictionary, POS dictionary, Ukrainian, VESUM, POS tagging, morphological
Morphology is critical for many downstream NLP tasks, and morphological lexicons have been
created for a number of different languages. They are especially useful for highly inflectional
languages and are the building blocks of spellcheckers and parsers. The output of a morphological
module is often exploited by NLP applications, such as search engines, information extraction
systems, and machine translation systems. The high utility and manifold applicability of a large
morphological dictionary is convincingly evidenced by such projects as MorfFlex CZ 2.0. Developed
stagewise for over 30 years, this Czech lexicon has more than 100,000,000 wordforms representing
over 1,000,000 lemmas [
Like other Slavic languages, Ukrainian is highly inflectional: one paradigm may consist of 17-19 forms for a typical noun, 27-32 for verbs (excluding analytical forms), and 32-43 for adjectives. Ukrainian inflectional morphology includes:
number: singular and plural, with occasionally used, even though generally archaic, forms of
2022 Copyright for this paper by its authors. • grammatical case: nominative, genitive, dative, accusative, instrumental, locative, and vocative, with a number of words having multiple possible forms for a given case; • person: 1st, 2nd, and 3rd; • tense: past, present, and future; • aspect: imperfective and perfective; • mood: indicative, imperative, and subjunctive; • degrees of comparison: positive, comparative, and superlative;
For various reasons, Ukrainian texts abound in spelling and morphological variants and idiosyncrasies, which greatly complicates the task of practical morphological annotation, even when the goal is to handle contemporary texts only. Extending the scope timewise to earlier periods and geographically to Ukrainian diaspora texts necessitates the use of a significantly richer set of morphological devices. There is a distinct need for a large machine-readable dictionary for morphological analysis that would be suitable for various types of texts, able to handle both standard and nonstandard usage, and providing good coverage in Ukrainian corpora. Our goal here is to explain how VESUM meets these challenges, describe the tools and methods underpinning its development, and analyze its practical application.
The paper is organized in the following way. In Section 2, we review the relevant works in the domain of Ukrainian morphology. Section 3 describes the composition and features of VESUM. Section 4 details the applications of VESUM, while the next section provides an account of how POS tagging is performed using VESUM. In Section 6, we discuss text coverage achieved with the help of VESUM. Finally, conclusions are drawn and prospects for future development are outlined.
Ukrainian is a synthetic language in that it expresses grammatical meanings through inflections
rather than word combinations. It has a significant degree of irregularity, especially with regard to
nominal declension and verbal conjugation. For this reason, an adequate morphological description
requires a large number of morphological classes and a number of exceptions to be specified. The
creation of a morphological lexicon is, thus, a challenging task, and the situation is compounded by
the fact that the existing descriptions of morphological paradigms for Ukrainian do not easily lend
themselves to use in NLP. Traditionally, such works single out classes based on both inflections and
stress patterns [19] and are, thus, more complicated than is practically necessary for POS tagging,
which does not involve accentuation. This approach is adopted in two academic grammatical
dictionaries of Ukrainian [
In the domain of practical NLP applications, a morphological tagset has been developed and
implemented for Ukrainian in an open-sourced project [
As a highly inflectional language, Ukrainian requires a morphological lexicon consisting of lemmas and codes to generate declension and conjugation paradigms, i.e., all the wordforms associated with a given lemma. For a long while, no resource of this type was publicly available for Ukrainian. VESUM [12] was created to fill this gap. In its current version 5.6.0, the dictionary contains over 416,000 lemmas from which over 6.5 million wordforms are generated. VESUM is a non-commercial project: the dictionary data are available under the CC BY-NC-SA 4.0 license, while its software is distributed under GPLv3.
VESUM has benefited from some of the best lexicographical and morphological resources
available for Ukrainian: an academic grammatical dictionary of Ukrainian [
ua_1992 (spelling under the 1991 rules) ua_2019 (spelling under the 2019 rules) var (variant form) bad (erroneous or objectionable lemma/wordform) rare (for items with markedly low frequencies).
Standard neutral vocabulary is left unmarked.
In addition to purely morphological and stylistic tags, VESUM utilizes several semantic tags. These labels are abbr (abbreviation) and prop (proper name) with further specification: prop:lname (last name), prop:fname (first name), prop:pname (patronymic name), prop:geo (geographical name), and prop:abbr (abbreviated proper name).
VESUM’s output is a flat list of wordforms in the format
wordform lemma positional tag For example, here is a fragment of the paradigm for the verb vesty (lead): вести verb:imperf:inf веди verb:imperf:impr:s:2 ведім verb:imperf:impr:p:1 ведімо verb:imperf:impr:p:1 ведіть verb:imperf:impr:p:2
Positional tags are strings of individual tags each of which encodes a morphological category. The tags are separated by the semicolon: verb, imperfective aspect, imperative mood, singular/plural number, infinitive/person in the example above. Unlike other morphological dictionaries, such as the MorfFlex Dictionary of Czech [18], the names of individual tags are mostly shortened English words. This transparency helps even casual users get a better grasp of the morphological annotation. They can then employ individual tags and their combinations to restrict search queries. This format also conveniently expresses morphological features that can be exploited by rules, taggers, and computer models. 3.2.
The distinct features of VESUM that are dictated by its practical orientation and set it apart from other morphological dictionaries can be summarized as follows: 1. Open-source project 2. Machine-readable format 3. Large size (bigger than similar resources) 4. A compact system of inflection codes 5. Dynamic nature (the dictionary is constantly enlarged with new lemmas and is used together with a dynamic tagging component) 6. Wide coverage of proper names: over 54,000 lemmas, including all names of populated areas in Ukraine according to the official register; Ukrainian geographical names introduced in the process of decommunization; more than 3,500 first names, 1,000 patronymic names, and 28,000 last names; a number of foreign proper names 7. Coverage of non-standard vocabulary: 8,000 erroneous lemmas (with replacements), 1,700 most frequent abbreviations, alternative spellings, 1,500 slang words, and over 1,200 archaic words 8. Inclusion of rare morphological forms, such as the colloquial infinitive forms ending in -t’ rather than -ty and the variant ending -a for the accusative case of some singular masculine nouns, e.g., ножа (knife.Acc.sing) 9. Information on case government, e.g., rv_oru after an adjectival lemma means that it governs a noun in the instrumental case 10. Suitability for expansion with other types of linguistic information (phonetic, semantic, etc.) to be applied in the course of text processing.
One of VESUM’s defining features is its practical focus and integration with several related
projects. The dictionary is geared toward practical application, handling real-life Ukrainian texts with
their complexities and irregularities, formalization of morphological information, and availability in
machine- and human-readable form. Its origins can be traced back to the ispell-uk project for
spellchecking under Linux. The dictionary was later adapted to perform more sophisticated spelling
and grammar checking in Pravopysnyk [17], the Ukrainian module of the LanguageTool language
checker [
One of the milestones in VESUM’s development came in 2017 when a new Ukrainian
morphological analyzer was created for the Apache Lucene search engine and the Ukrainian-language
Wikipedia articles were re-indexed. Since then, full-text search based VESUM’s morphological data
has been used also in other web projects. The morphological toolkit containing VESUM has been
used in the lang-uk project [
The most challenging material for VESUM as a dynamic morphological tool has been presented by the General Regionally Annotated Corpus of Ukrainian (GRAC) [14], which is the most diverse corpus of Ukrainian, running a total of over 650 million tokens, spanning over two centuries (18162021), composed of over 90,000 texts in various genres written by 20,000 authors who used different spelling systems. VESUM and GRAC form a dynamic tandem: iteratively, VESUM is used to lemmatize and POS tag each new version of GRAC; a list of unrecognized words, sorted by frequency, is then generated from the tagged corpus; new lemmas are extracted by expert linguists from this list, semi-automatically coded, manually verified, and added to VESUM. Subtle modifications have been made in the grammatical apparatus to enable it to handle irregular forms, archaic words, alternative spellings, etc. Over the years, this approach has been mutually beneficial: GRAC has received increasingly better-fitted POS tagging, while VESUM has grown and improved its coverage by drawing lexical items from a wide variety of textual sources.
VESUM is highly sensitive to language change: it includes new geographical names that became official in Ukraine as a result of the 2015 decommunization laws, feminine forms of nouns that have gained currency over the past several years, and morphological and spelling changes introduced in the new official spelling rules of 2019.
While VESUM is primarily intended for machine use, it can also be highly useful to anyone interested in Ukrainian morphology and inflection, to both native speakers and non-native students of Ukrainian. We have developed a web interface for VESUM available at r2u.org.ua/vesum to function as an online grammatical dictionary for a wide audience of human users. Search queries can be adapted (via a checkbox) to focus on lemmas or specific indirect forms. Question marks and asterisks can be used in queries to replace, respectively, one character and zero or more characters. VESUM has evolved over the years to include various forms, such as substandard and archaic forms, that are not normally presented in academic dictionaries of Modern Ukrainian. Figure 1 below illustrates that a typical paradigm for an adjective, such as зелений ‘green’, includes long forms (зеленая, зеленую, зеленеє. зеленії) and the short form зелен, which are missing from other such dictionaries. However, they occur in older texts, in elevated speech, in poetry, and in some other instances. Thus, the textbased approach persistently implemented in the compilation of VESUM for an extended period of time leads to enhanced coverage of real language phenomena as compared to other similar resources.
The web interface also provides quick links that let the user look up the word in question in collection of Russian-Ukrainian and English-Ukrainian dictionaries, in an explanatory dictionary of Ukrainian, and in the GRAC corpus. Moreover, there are links to the full tagset used and statistics.
Other uses of VESUM include the compilation of various types of dictionaries, linguistic research, NLP research, and so on.
A static morphological dictionary can hardly be expected to comprehensively cover the multitude of words, such as hyphenated adjectives (for example, українсько-англійський ‘Ukrainian-English’) or nominal compounds that are created using active patterns of the language in question. To this end, VESUM has been supplied with a dynamic tagging component that processes lexical items of this kind in Ukrainian texts. Ukrainian has a number of combining forms, such as бізнес- ‘business’ and онлайн- ‘online’, which are joined with other words with a hyphen, e.g., онлайн-магазин ‘online store’. The dynamic tagging component recognizes these and several other types of hyphenated nouns, adjectives, and adverbs with 95% accuracy [17].
VESUM comes together with a set of disambiguation rules that remove a limited number of ambiguous forms based on frequency information and context. The overall task of ambiguity resolution is to be dealt with at a separate stage.
For POS tagging, VESUM is converted into the morfologik format [
For anyone interesting in POS tagging Ukrainian texts using VESUM, the LanguageTool API NLP UK project, available from github.com along with VESUM, provides the TagText utility, along with a tokenizer and a lemmatizer for Ukrainian. TagText calls LanguageTool functions and the Ukrainian dynamic tagging module to perform sentence splitting, lemmatization, POS tagging, and disambiguation. Several hundred cases of ambiguity are also resolved. The user has a choice of receiving TagText’s output in text form or XML and collecting several types of statistical data. The tagged version of Ukrainian text can then be used as input for disambiguation based on transition probabilities and neural networks.
Below is a fragment from the Constitution of Ukraine POS-tagged by TagText with output in xml format:
As can be seen, the tagger has not performed disambiguation for these tokens. Only a handful of disambiguation rules are implemented in the tagger, and work continues on full-fledged disambiguation.
A practical NLP researcher is interested in text coverage, i.e., what percentage of tokens in a given text are recognized by a morphological tagger. To this end, we have generated statistics by using the TagText tagger on Ukrainian texts after filtering out Russian words. The results are presented in Table 1.
Five corpora (scientific texts, fiction, news, a random GRAC sample, and the Wikipedia corpus
from the lang-uk project) have been processed. On non-encyclopedic texts, VESUM achieves a
consistent rate of 97-99% in terms of wordforms. The rates of recognized types exhibit greater
variance: 76% for scientific texts and fiction; 82% for the GRAC sample, and 85% for news. The
Wikipedia corpus [
Bogdan Babych [
From our experience of processing various large Ukrainian text corpora, the tail of frequency
distribution of unrecognized types is composed predominantly of 1) proper names; 2) misspellings
and Russian words (written in Cyrillic, which in many cases makes them graphically indistinguishable
from Ukrainian words); 3) foreign (mainly English) words written in Latin script. Fiction texts may
also contain a number of archaic words and spellings. Given a sufficiently large corpus, especially
collected from the Internet, unrecognized types in group 2 may achieve frequencies above 10 or
higher. An algorithm for automatic paradigm induction, such as suggested in [
VESUM is aimed at handling diverse but legitimate Ukrainian vocabulary. It does cover thousands
of lemmas that are outside the standard language, but no attempt is made to cover outright
misspellings, Russian vocabulary, or words in Latin script. That said, VESUM’s coverage of proper
names can be improved in two ways: by adding the more frequent ones to VESUM and by
complementing the lexicon with an algorithm along the lines of [
In contrast to other resources for Ukrainian, VESUM is a large dictionary with wider coverage of the Ukrainian word stock, including proper names, abbreviations, non-standard wordforms and lemmas, slang, alternative spellings, and dialect and archaic words. VESUM supplies a series of stylistic and semantic labels, and its efficiency is increased with the help of a dynamic tagging module. VESUM has an accompanying toolkit for the morphological analysis of Ukrainian.
The dynamic tagging module can be enhanced with techniques similar to those suggested in [
The morphological dictionary can be complemented with a semantic lexicon to enable both morphological and semantic tagging of Ukrainian texts in one pass.
Overall, VESUM is a powerful open-access source of morphological data for Ukrainian that is already used in several large-scale projects. It achieves high text coverage on various types of texts and can be effectively used in computational linguistics research and NLP applications. It also serves as a rich source of morphological data to a wide range of users via a searchable web interface. With its practical text-oriented approach and growing lemma count, VESUM is a useful and dynamic tool for the evolving Ukrainian language.
[12] A. Rysin and V. Starko. Large Electronic Dictionary of Ukrainian (VESUM). Version 5.6.0.
2005–2022. URL: https://github.com/brown-uk/dict_uk [13] Russian-Ukrainian Dictionaries. Comp. by A. Rysin, V. Starko, Yu. Marchenko, O. Telemko et al. 2007–2022. URL: https://r2u.org.ua [14] M. Shvedova, R. von Waldenfels, S. Yarygin, A. Rysin, V. Starko, T. Nikolajenko et al. GRAC: General Regionally Annotated Corpus of Ukrainian. Electronic resource: Kyiv, Lviv, Jena. 2017–2022. URL: http://uacorpus.org/ [15] V. Shyrokov et al. Korpusna linhvistyka [Corpus Linguistics], Dovira, Kyiv, 2005. [16] V. Shyrokov et al. “Slovnyky Ukrainy” online [“Dictionaries of Ukraine” online], 2001–2022.
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