Developing an Online Kazakh-English-Russian Thesaurus of

Industry-Specific Terminology

Ainur T. Bayekeyeva

, Saule Zh. Tazhibayeva

, Aigul A. Shaheen

, Zhainagul S.

Beisenova

, Gulnar Beysenkyzy Mamayeva

Abstract

Industry-specific translation is one of the rapidly developing

and highly demanded sectors in Kazakhstan. This paper

discusses the theoretical and methodological issues of

compiling a controlled multilingual vocabulary or thesaurus

for the purposes of industry-specific translation. The

proposed multilingual thesaurus addresses the gap of existing

online dictionaries with the lack of ability to translate directly

from English into Kazakh, and provides relevant equivalents

for mining and metal terms in three languages: Kazakh,

English, and Russian. The study is interdisciplinary and

combines methods of linguistic analysis, machine learning,

ontological and corpus-based studies that allow an exhaustive

analysis, generalization, comparison, systematization,

classification, and formalization of the mining industry

terminology through a multilingual parallel corpus based on

the Zthez international technical platform. The controlled

multilingual thesaurus is designed to promote intercultural

communication of professionals and translators in the mining

industry. Besides it enables the foundation to be built for a

Kazakh language corpus, unifying and systematizing Kazakh

industry-specific terms in a multilingual way.

PhD Candidate, Email: a.baekeeva@rambler.ru (Corresponding Author)

Tel: +77-477825011

Professor, Email: [email protected]u

Associate Professor, Email: akingan@mail.ru

Associate Professor, Email: zhaina_b@mail.ru

Associate Professor, Email: gulnar.[email protected]

L.N.Gumilyov Eurasian National University, Republic of Kazakhestan

http://dx.doi.org/10.22034/ijscl.2022.543082.2465

ARTICLE HISTORY:

Received December 2021

Received in Revised form February 2022

Accepted February 2022

Available online March 2022

KEYWORDS:

Controlled vocabulary

Terminology

Interoperable thesaurus

Industry-specific translation

Multilingual thesaurus

Developing an Online Kazakh-English-Russian Thesaurus of Industry-Specific Terminology

1. Introduction

There has been an increased interest in issues

related to intercultural communication within

specific professions (Bloschchynskyi et al.,

2021). Industry-specific translation (IST)

serves as a cross-subject science between

theory and practice in translation for industry-

specific terminology, especially due to the

impact of the ongoing global pandemic on the

world’s economy and other related industries,

including translation services. State bodies and

ministries, educational establishments, and

schools and universities have turned home to

offices, so the need for online resources has

significantly increased. At the same time, IST

is one of the most difficult and laborious

translation services that requires translators’

high qualifications and knowledge of a certain

subject area. A technical translator needs to be

extremely aware of high language acquisition

and academic writing skills and have a good

sense of both the Source Language (SL) and

Target Language (TL); the core requirements

rely especially on gaining depth in the

knowledge and skills of technical thinking and

terminology.

The innovative technologies applied in

translation studies implementing the objectives

of the State Programme “Digital Kazakhstan”

are forcing Kazakhstan’s translators, linguists,

Turkologists, and industry-specific terminologists

to make a new quantum leap. In the

digitalization period, it is important to create a

new generation of dictionaries that meet

modern topical challenges. One of these

dictionaries is a controlled multilingual

vocabulary or thesaurus on subject areas jointly

developed by linguists and experts in

technology information corresponding to the

subject fields. Industry-specific terms in the

Kazakh language are urgently needed to fix,

regulate, and identify semantic equivalents in

Russian and English. Thesauri in various

subject areas are necessary for quick

information retrieval with the accurate semantic

translation of industry-specific terms not only

for translators but also for all interested experts.

The mining industry has received a new

development impetus since Kazakhstan gained

independence. Many metallurgical plants and

complexes started applying modern advanced

technologies for exploration, geology,

production, and processing. The terminological

base of mining and metal terms has been

enriched with new terms related to

technological processes, while the original

Turkic Kazakh terms have become less used. At

the same time, the mining and metallurgical

industry, as well as the professions associated

with them, occupies a special place in the Atlas

of New Professions and Competencies of

Kazakhstan. The Terminological Committee of

Kazakhstan carries out activities to arrange new

terms in all sectors and industries, publishing

hardcopy Kazakh-Russian terminological

dictionaries. However, industry-specific terms

are not always correctly interpreted by linguists

and translated into Kazakh or Russian.

Moreover, the translation of terms is often not

accurate, with a variety of synonyms that make

it difficult for the translator to understand and

choose only the one semantically correct

equivalent.

Therefore, one of the important objectives of

this research is to systematize new international

terms and document language material related

to the Turkic lexical layer in a modern

interoperable platform. In this regard, the study

of Kazakh mining and metal terms is of

particular relevance. Mining terminology was

first adopted and developed by Satpayev in

1957. However, since then, the terminological

base has not been regularly and systematically

updated. Modern Kazakh mining and metal

terms have been enriched by international terms

that do not reflect their semantic content.

Satpavev´s approach to compiling Kazakh

terms is artificial and leads to a functional

limitation of their use in practice. Now, we have

to be ready for modern challenges and create

terminological dictionaries based on the

semantic concepts in various knowledge fields,

one of them being the mining industry.

Translating technical texts for industries is now

one of the most popular types of translation

services in Kazakhstan. This type of translation

has a number of features. First of all, it requires

not only the knowledge of industry-specific

terms applied in a certain subject area, e.g., the

mining and metallurgical industry, but also of

related areas such as geology, enrichment,

beneficiation, refinement, and so forth. Besides,

the technical translator must focus on mining

and metal terms in a general way and offer

clear, exact details in exploration, development,

enrichment and beneficiation, equipment and

A. T. Bayekeyeva et al./ International Journal of Society, Culture & Language, 10(1), 2022 ISSN 2329-2210

technology, and other issues of the mining

industry.

The role of the Kazakh language in science and

technology texts remains in the shade since

Russian is the dominant language for IST. In

addition, modern controlled interoperable

thesauri are usually monolingual, so the lack of

English-Kazakh and Kazakh-English dictionaries

in subject areas is a serious problem for

professionals and translators. Thus, when

searching in online dictionaries, the absence of

trilingual options, i.e., English-Russian-Kazakh

creates difficulties, not only for professionals

and translators but for all Automated

Information System (henceforth AIS) users in

related industries. Many trilingual industry-

specific dictionaries are available only in hard

copy, and in the current pandemic situation, all

AIS users should be given an equal opportunity

to access these dictionaries regardless of their

location. Therefore, there is an urgent need to

create a systematized controlled multilingual

and interoperable thesaurus to promote

communication and interaction between

professionals, translators, and AIS users in

industry-specific areas and to offer them a way

to freely use special terminology, provide

adequate translation in specific subject areas,

and find the necessary data related to a

particular industry-specific term without

having to search several dictionaries for the

relevant information and accurate terminology

in order to avoid misunderstanding and

mistranslation.

Rapidly growing economic cooperation in

Kazakhstan makes it necessary to enrich the

terminological base with various new terms

denoting technology and equipment. Direct

English-Kazakh translation occurs very rarely.

For this reason, creating a new generation of

dictionaries will enhance opportunities for

Kazakhstan’s translation services and

strengthen the status of this language as a state

one.

The purpose of this investigation is to explore

the terminology of the mining industry and

compile a controlled Kazakh-English-Russian

multilingual thesaurus related to this subject

area. The analysis of issues related to thesauri is

a new interdisciplinary study at the intersection

of translation studies, computational linguistics,

Turkology, terminology, and information

technology. This interdisciplinary and cross-

subject research has the following objectives:

 to study the ways of forming Kazakh mining

and metal terms;

 to identify and document the common

Turkic layer of vocabulary in Kazakh

mining terminology;

 to systematize new international terms that

are actively enriching the terminological

base of Kazakh industry-specific terms; and

 to identify semantic equivalents in

translating special terms into English and

Russian.

This paper considers more than 10,000 Kazakh

mining and metal terms provided by the

Terminological Committee of Kazakhstan. The

proposed multilingual thesaurus is shown to

provide relevant equivalents of three languages

in one data scheme: Kazakh, Russian, and

English. The paper demonstrates the use of the

controlled multilingual thesaurus in the Digital

Library (DL) that enables the user to search for

a faithful translation of industry-specific terms.

This also lays the groundwork for the future

development of the Kazakh-language corpus

and for the unification and systematization of

industry-specific Kazakh terms in a

multilingual way.

2. Theoretical Framework

2.1. Industry-Specific Translation

Translation of scientific and technical literature

differs greatly in translation methods from

those of literary works. A literary translator

may be perceived as a portrait painter who

aspires to portray rather than show a

photographic similarity (Bayekeyeva et al.,

2020). Scientific and technical translators’

quality work depends mainly on the vocabulary

(terminology), which tends to be univocal and

have ready-made equivalents, and on the use of

language style to transfer image accuracy

(Franco, 2004). It can be said that fiction

translation is associated with the field of art,

while technical translation refers to the field of

science.

IST starts from developing a special

terminological base, which is why a thesaurus

in the DL is compiled to solve the industry term

systematization. Bayekeyeva et al. (2020)

define the DL as “a system for managing

structured cataloged collections that provides a

Developing an Online Kazakh-English-Russian Thesaurus of Industry-Specific Terminology

comprehensive search of dissimilar digital

resources” (p. 1870). In this sense, the major

purpose of compiling a thesaurus is directly

related to information support in scientific

research and translation activities; it also has to

do with the formation and development of its

own IST electronic resources through the

interoperable management of publications and

bibliographies. Bayekeyeva et al. (2020)

discuss the theoretical and methodological

issues of compiling a multilingual thesaurus for

conducting IST in the mining industry. They

describe the facts which translators deal with

for providing adequate translation when facing

industry-specific terms in real texts.

2.2. Diachronic Analysis of Traditional

Dictionaries of Industry-specific Terms

Practical, empirical preconditions for the

systematization of industry terms began in the

1920s, and this is evidenced by the

systematization and publication of various

industry terms in dictionaries directly related to

the development of scientific and technological

progress in Europe; for instance, see Fay (1920).

Terminology, which involves the study and

compilation of terms belonging to specific

fields, has attracted the attention of many

Kazakh scholars such as Kaidarov (1993),

Baitursynuly (2009), and Aitbayuly (2013).

The theoretical and practical aspects of forming

industry-specific terms have been investigated

by domestic terminologists, among them

Abdіrasіlov (1999), Isakova (2000), Kaliuly

(2008), Beisenova (2011, 2014), and

Kurmanbayuly (2014), as well as foreign

linguists Lotte (1961), Reformatsky (1961),

Cabrė (1998), Leichik (2009), and

Superanskaya (2012). All these researchers in

terminology noted the need to arrange industry-

specific terms and made attempts to compile

traditional dictionaries.

The development of terminology is an

independent scientific field that studies the

basis of branch translation in linguistics terms

and dates back to the 1930s (Cabre, 1998). Due

to the rapid development of industrialization,

industry-specific terms began to form in the

Kazakh and Russian languages. Before the

emergence of multilingual dictionaries of

Kazakh industry-specific terms, the first

dictionaries were compiled in short versions or

glossaries by Omarov (1923) in Physics subject

words, and Karatyshkanov (1927) in Subject

terms; they were published in Orenburg,

Moscow, and Kyzylorda. In this sense, bilingual

dictionaries of Russian/Kazakh industry-

specific terms began publishing Russian-

Kazakh military words (1926), Dictionary of

names (1931), Terminological dictionary (1931),

and Terms of the Kazakh language (1935).

More than 150 terminological dictionaries were

published in Kazakhstan from 1940 to 1990.

Between 1991 and 2003, more than 100

dictionaries were compiled and published, such

as Explanatory dictionary of the Kazakh language

published 1974–1986, Phraseological dictionary

of the Kazakh language (1977), Russian-

Kazakh dictionary of terminology (Ámіrbaev et

al., 1959), Dictionary of the Kazakh language

(1999), and the Dictionary of Turkic languages

(Oztopcu et al., 1996).

In the second half of the 20th century, from

1959 to 1995, other Russian-Kazakh

terminological dictionaries were developed

relating to various subject fields different from

the mining industry, such as geology

(Mashanov et al., 1960), mechanism and

machinery (Joldasbekov & Ábdіrahmanov,

1968; Serıkbaev et al., 1974), chemical terms

(Bіrіmjanov & Omarov, 1974), agricultural

mechanization (Myńbaev et al., 1983), water

engineering terms (Ábdіrahmanov & Manabaev,

1991), hydrogeology and engineering geology

(Sydyqov & Qabıev, 1993), and theoretical

mechanics (Joldasbekov & Saǵıtov, 1994).

Furthermore, during this time, there also were

Russian-Kazakh dictionaries for the mining

industry, specifically on metallurgy

(Ábdіrahmanov & Býketov, 1959) and physics

(Bakaev et al., 1962; Mashanov et al., 1959). In

the 2000s, a 31-volume series of 155.000 words

of Russian-Kazakh and Kazakh-Russian

industry-specific terminological dictionaries

were published and approved by the

Terminological Committee (Kurmanbaiuly &

Sapina, 2004). There were also dictionaries and

thesauri related to architecture and construction

(Qulmanov, 2009), information systems

(Ilyasova, 2010), ship construction (Koyanbayev

& Sabirova, 2013), polygraphic terms

(Medeubekuly et al., 2013), legal terms

(Omashuly, 2013), post terms and phrases

(Toksanbay, 2013), veterinary terms

(Djanabekov & Djanabekova, 2013), oil and

gas terminology (Makhambet, 2015), and mass

media and telecommunication terms (Tursyn,

A. T. Bayekeyeva et al./ International Journal of Society, Culture & Language, 10(1), 2022 ISSN 2329-2210

2015). However, in spite of the recent

development in the mining industry, no new

dictionaries of mining and metal terms have

been published for almost two decades.

2.3. Kazakh-language Corpus and Thesaurus

Compilation

In recent years, the Kazakh language has

become an object of major concern to linguists.

Several scholars have attempted to make up a

corpus of the Kazakh language that would be of

great significance in natural language

processing tasks, including information

retrieval and machine translation. One of the

first attempts to compile a Kazakh corpus was

made in 2013; it contained more than 135

million words belonging to five different

stylistic genres (Makhambetov et al., 2013).

Rakhimova and Zhumanov (2017) created a

multilingual parallel corpus of general words in

the Kazakh, Russian, and English languages

using the Bitextor application and demonstrated

how dictionaries could be enriched with new

words without special linguistic knowledge.

Numerous researchers have contributed to the

informatization of natural language processing

of the Kazakh language. Thus, Altenbek and

Sun (2010) applied N-gram model methods and

rule-based methods to extract noun phrases

from Kazakh-language texts. Bekbulatov and

Kartbayev (2014) focused on the internal

morphological structure of Kazakh sentences

and statistically demonstrated the impact of

morphological preprocessing on the quality of

Kazakh-English machine translation. Tukeyev

and Karibayeva (2020) constructed a system of

Kazakh word endings for effective morphological

segmentation. Automated processing tools and

algorithms were developed for the KazNLP

platform to deal with texts in the Kazakh

language (Yessenbayev et al., 2020).

Despite the rapid development of translation

theory, mining and metal terminology have not

been given due attention. The uniqueness of the

Kazakh language in rubrics of online industry-

specific terminology is manifested in the fact

that the original Kazakh terms of the mining

industry constitute a rich lexical layer for

providing the names of metals and minerals.

New, borrowed international terms normally

indicate the names of equipment and

technologies. In English and Russian, instead of

industry-specific terms, as a rule, abbreviated

forms of nomenclature of chemical elements

are frequently used, e.g., Au, Ag, Cu, Fe, Zn,

etc. When translating scientific and technical

documents, such as industry-specific texts in

Kazakh, Russian, and English, written

documentation with certain additional features

is needed. This study suggests using a controlled

vocabulary or thesaurus for translation purposes.

A thesaurus is a comprehensive online

dictionary of industry-specific terms, compiled

in an interoperable system with links, which

includes several types of dictionaries such as a

glossary, bilingual dictionary, multilingual

dictionary, synonymic dictionary, and

terminological dictionary. It is one of the major

tools in translation theory and practice,

particularly in compiling various dictionaries

and glossaries for specific fields and purposes,

which require the participation of a wide range

of professionals in linguistics, information

technology, related branches of science and

technology, and so forth. The compilation of

monolingual thesauri of special terminology

has been considered by a number of researchers

in various scientific areas. Aleshinskaya and

Albatsha (2020) focused on methodological

issues and suggested a cognitive model of

compiling a monolingual terminological

thesaurus in computer science. Heiradi et al.

(2020) compiled a corpus of academic words

belonging to the pharmacy domain. Niyazbek

and Talp (2019) contributed to the construction

of a Kazakh terminology recognition platform

in information technologies through a conditional

random field and manual modification. Aitim et

al. (2020) developed a complex methodology

for generating a completely automatic

thesaurus of Kazakh-language specialized

vocabulary that would increase the

effectiveness of natural language processing.

A controlled dictionary is an interoperable

dictionary that meets professional requirements

for information retrieval and machine

translation. The issues of creating a controlled

thesaurus of the Kazakh language have been

studied by domestic and foreign scholars in

various aspects. Kazakh-English parallel

models and constructions have been studied and

adopted for machine translation. For example,

Kartbayev (2015) attempted to improve random

Kazakh-English parallel corpora in terms of

phrase tables by reducing the word alignment

error rate. In methods of extending machine

translation resources, Rakhimova and

Zhumanov (2017) demonstrate how transfer

Developing an Online Kazakh-English-Russian Thesaurus of Industry-Specific Terminology

rules can be automatically learned from a

parallel corpus. Two parallel Kazakh-English

corpora KAZNU and WMT19 were explored in

terms of solving the problem of unknown words

for neural machine translation (Turganbayeva

and Tukeyev, 2020). Akhmed-Zaki et al. (2021)

developed several preprocessing tools to

generate word forms and handle morphological

ambiguity.

The problems of creating bilingual and

multilingual thesauri have been investigated by

a number of researchers such as Ahmad and

Gillam (2005), Mansurova et al. (2017), and

Niyazbek and Talp (2019). They focused on

designing and developing a media-corpus for

the Kazakh language and for recognition

systems. Moreover, grammatical, syntactical,

and lexicological issues have been studied from

the perspectives of the parsing model of Kazakh

sentence structure (Sharipbay et al., 2019;

Yerimbetova, 2016) and Kazakh morphology

(Yelibayeva et al., 2019). Creating a controlled

multilingual thesaurus, including Turkic

languages, has been considered for ontology in

information technology (Fedotov et al., 2016;

Sambetbayeva et al., 2016). Thesauri in modern

applied sciences such as WordNet, EuroWordNet,

or Wiktionary linguistic resources describe the

relationship between lexical meanings of

natural language as a hierarchical system of

synonymic groups, i.e., synsets (Tussupov et

al., 2016).

The review of all this scientific literature

inherent to the research topic of this paper

reveals that a comprehensive study of mining

and metal terms in multisystem languages has

not been previously conducted, and as the

evidence suggests, it is extremely necessary. So

far, multilingual online thesauri researches of

mining industry-specific terms have been

developed neither in Kazakhstan nor abroad. In

this respect, it is of the utmost significance to

compile a controlled multilingual Kazakh-

Russian-English thesaurus for the mining

industry that would be of practical value in

translation.

3. Methodology

3.1. Materials

To ensure industry-specific terms in mining and

metal from Kazakh, Russian, and English, it

was decided to use the universal Integrated

Distributed Information System (IRIS) to

compile the thesaurus developed by the

Institute of Computer Technology and Science

of the Siberian branch of the Russian Academy

of Sciences in 1998 (Fedotov et al., 2016).

3.2. Procedure

This section describes all the steps used to

identify, systematize, and compare mining

terms for the controlled thesaurus.

The first step is the material selection drawn

from a sample of Kazakh terms belonging to the

mining industry. More than 10,000 units were

selected from bilingual and multilingual Kazakh

industry-specific dictionaries (Termincom.kz).

The equivalent translation term is based on data

from multilingual industry-specific dictionaries

(Qudaibergenov, 2009) and English-speaking

countries (Fay, 1920; Hornby, 1995; Encyclopedia

Britannica, 1998), as well as online resources

such as Sozdik (https://sozdik.kz/) and

Termincom (http://termincom.kz/termins).

The second step is parsing the website and

compiling and saving information easily

(Khairova et al., 2019) in the analysis of digital

sources for terminological and industry-

specific dictionaries. The most actively used

sites for Kazakh translation are Multitran

(https://www.multitran.com/), Sozdik (https://

sozdik.kz/), and Termincom (http://termincom.

kz/termins). This study shows the challenges

that Kazakh translators face when translating

mining industry terms to Russian and English.

The third step is related to the analysis of the

collected data using the Zthes data scheme. This

is a family of specifications that enables the

representation of thesauri and facilitates

interoperability for applications dealing with

thesauri (http://zthes.z3950.org/). This tool also

enables the creation of a thesaurus for the

mining industry that unifies and systematizes

industry-specific Kazakh terms in conformity

with the requirements of modern interoperable

thesauri. Thus, the interoperability is shown as

an easily integrated way to communicate in the

other language that really helps describe and

provide Russian and English equivalents, as

well as classify the terms into relevant topics

using related rubrics and associated relations in

a hierarchical order.

3.2. Compiling an Industry-Specific Thesaurus

The research is mainly based on linguistic

analysis methods that enable the creation of an

A. T. Bayekeyeva et al./ International Journal of Society, Culture & Language, 10(1), 2022 ISSN 2329-2210

exhaustive analysis, generalization, comparison,

systematization, classification, and formalization

of mining industry terms. This method was used

to (a) systematize the mining and metal terms

of the Kazakh language, (b) identify features in

forming Kazakh mining terminology, and (c)

perform a comparative analysis with similar

terms in English and Russian. Formalizing and

locating are implicit in the translation process

when adapting the borrowed terms to Kazakh.

To create a controlled thesaurus, supportive

methods of machine translation were used, such

as automatic rubricating, object, and relation,

creating ontologies of the subject area. To

guarantee reliable results, other supportive

methods such as statistics and documentation

were applied. In this way, there is an integration

of methods that combine interdisciplinary and

cross-subject research relations.

Furthermore, to analyze and systematize

mining industry terms, a multilingual parallel

corpus for Kazakh-Russian-English is used.

The terms are taken from Kazakh and translated

into Russian and English, respectively. A

parallel corpus is particularly important in

studying language, and translation features

since it provides precision and accuracy in the

equivalent analyzed lexicon through machine

translation (Khairova et al., 2019).

Some previous research has approached the

ontological and computational study of

bilingual and multilingual thesauri for the

mining industry and other related fields,

focusing on particular linguistic aspects.

Ontological studies establish a clear and

decisive relationship between concepts and

categories of the studied subject area. For the

mining industry field, ontology is a set of

concepts and statements about their

classification, relations between them, and the

hierarchy on the “general-part” and “part-

whole” relations (Bayekeyeva et al., 2020).

During this research, it was extremely

necessary to consider the conceptual

methodology aspects in a systemic way and

manifest them as a unity of “whole-part”,

“external-internal”, “static-dynamic”, “cause-

effect”, and “communication process”, among

others.

Computational studies also offer a great

contribution to the development of the present

research, especially with the use of its tools that

provide proven accuracy in the results and also

facilitate the organization and development of

the research process. Accordingly,

Kuandykova et al. (2014) constructed an

English-Kazakh parallel corpus at the School of

Mechanics and Mathematics and created a

statistical machine translation system to present

problems and solutions to legal texts. In the

same way, Myrzakhmetov and Makazhanov

(2016) present an initial experiment on Russian

to Kazakh phrase-based statistical machine

translation (SMT) through a parallel corpus

based on morphological processing techniques.

They state that “machine translation from

Russian to Kazakh poses certain challenges of

both linguistic and technical nature” (p. 153).

These researches help the present paper as a

baseline to support the study of a controlled

vocabulary in DL: terminology, translation, and

thesaurus for Kazakh-Russian-English

languages in the mining industry field.

4. Results

4.1. Digital Sources for Terminological and

Industry-Specific Dictionaries

Due to the rapid development of computer

technology, professionals in the field of IST

have used a variety of electronic dictionaries,

including ABBYY Lingvo, DICT, FreeDict,

Free On-line Dictionary of Computing,

WordNet, Multilex, etc. Among the electronic

dictionaries most actively used by Kazakh

translators are Multitran (https://www.

multitran.com/), Sozdik (https://sozdik.kz/),

and Termincom (http://termincom.kz/termins).

However, when searching for the necessary

terms, Kazakh translators come across

multifaceted issues connected with using

trilingual contexts.

A serious problem is the lack of direct Kazakh-

English online dictionaries and a Kazakh-

language corpus for industry-specific contexts.

Existing electronic databases such as Sozdik,

Multitran, and Termincom do not always meet

the requirements for a quick search of

information. Translators particularly use

Kazakh-Russian dictionaries for Kazakh-

Russian bilingual texts (see figures 1 and 2).

Developing an Online Kazakh-English-Russian Thesaurus of Industry-Specific Terminology

Figure 1

Web Page of Kazakh-Russian Sozdik Online Dictionary

A. T. Bayekeyeva et al./ International Journal of Society, Culture & Language, 10(1), 2022 ISSN 2329-2210

Figure 2

Web Page of Kazakh-Russian Terminological Dictionary by Terminological Committee

Translators have to use Russian-English

dictionaries for Russian-English bilingual texts

(see Figure 3). So, in order to translate the texts

from Kazakh into English, translators utilize

two different dictionaries because of the

absence of trilingual dictionaries.

Figure 3

Web Page of Russian-English Online Dictionary

Developing an Online Kazakh-English-Russian Thesaurus of Industry-Specific Terminology

In order to face the Kazakh translators’ reality

and to give an opportune answer to the

problems mentioned above, this study presents

a clever and convenient solution that consists of

creating a new generation of multilingual

Kazakh-Russian-English dictionaries. In this

regard, it is necessary to immediately study,

systematize, and give a scientific description of

industry-specific terms in the Kazakh language.

The Zthez international technical platform,

tested by the Institute of Computational

Technologies SB RAS, has been chosen for the

compilation of a thesaurus of industry-specific

terms in DL (http://db4.sbras.ru/elbib/data/

admin/adm.phtml). The members of the

research group represent in Kazakhstan the

traditions of the linguistic science school and

the IT technology and science school of the

Siberian branch of the Russian Academy of

Science (see Figure 4).

Figure 4

Web Page of the Thesaurus of Industry-specific Terms in Digital Library

Developing a thesaurus contributes to the

creation of an online database of industry-

specific terms of the Kazakh language, with the

most accurate semantic equivalents, synonyms,

associate ranges, and other empirical material

for the further enrichment of the Kazakh

language corpus with texts, metadata, and

translations of materials into English and

Russian. The main advantage of this

multilingual thesaurus is in its interoperable

characteristics, so this thesaurus can be easily

integrated into international databases such as

the UNESCO, NISO, and LOGOS thesauri,

compiled in accordance with the international

standards (see National Information Standards

Organization, 2003, 2005; IFLA, 2009).

4.2. Controlled Multilingual Thesaurus of

Mining Terms

Industry-specific terms should provide a clear

and accurate reference to real objects and

phenomena, establishing an unequivocal

understanding of the transmitted information by

professionals. Therefore, a special requirement

is imposed on these types of words. While

considering the terms, it is necessary to bear in

mind that, first of all, the term has the exact

meaning in each field of study, i.e., it has a

strictly defined meaning, which can be revealed

by a logical definition, establishing the place of

the designated concept by the term in the

conceptual systems of a certain industry,

science, or technology.

Gradually, the content of technical knowledge

of the source language (SL) begins to penetrate

the signs of the target language (TL) and enrich

its vocabulary. In any language, the word or

phrase is already inseparable from its meaning,

and here the content of technical knowledge

becomes an element of the language in a certain

field, in this case, the mining industry. The

technical knowledge which has found its

expression in a word, in a term of SL, passes

into a qualitatively new stage, joining the

A. T. Bayekeyeva et al./ International Journal of Society, Culture & Language, 10(1), 2022 ISSN 2329-2210

semantic structure of TL, becoming a

component of the terminological system of the

given language.

Based on the foregoing, it can be concluded that

industry-specific terms evolved over a long

time and have now formed a strict

terminological system. Within this system,

certain forms of term building have been

created, the degree of productivity of which

makes it possible to determine the dynamics of

growth of terms and further means of their

development. In connection with the progress

of industry, science, and technology, where

new concepts are constantly being opened, it is

necessary to use more and more new terms in

the English, Kazakh, and Russian languages.

Term building takes place both at the expense

of the resources of the English language itself

and by borrowing from other languages. This

process allows language development and

makes the terminology international, which

allows scientists and professionals to

understand each other better.

The ongoing research focuses on compiling an

interoperable, controlled multilingual thesaurus

for translation and terminology, and makes a

contribution to the Kazakh language corpus of

industry-specific terms. As a result of this

study, major rubrics have been created for about

10,000 Kazakh terms related to the mining and

metal industry. The terms in the proposed

thesaurus are listed as a result of the analysis of

more than 5,000 documents developed in

Kazakhstan’s mining projects (Tau Ken

Samruk, its subsidiaries Tau-Ken Altyn, Tau-

Ken Temir, Shalkiya Zinc, Silicon Mining,

Masalsky GOK, Altyntau Kokshetau, Alaigyr,

Spassk, etc.). All the terms of “Mining and

Metallurgy” are grouped into the following

rubrics: “Mining and Metals”, “Minerals”,

“Exploration”, “Production”, “Equipment and

Technology”.

The proposed multilingual thesaurus provides

relevant equivalents for three languages in one

data scheme: Kazakh, Russian, and English. As

a major translator’s tool, the controlled

multilingual thesaurus is a collection of

information (corpus, arch) encompassing with

maximum fullness the concept, definitions, and

terms of a special field of knowledge or

industry, with examples in real contexts, i.e.,

their use in texts. It is a particular type of special

vocabulary in which semantic relations

(synonyms, antonyms, paronyms, hyponyms,

hyperonyms, and so forth) between lexical units

are indicated.

The controlled multilingual thesaurus in the DL

designed for IST comprises at least three

elements:

 a list of structured and systematized terms,

placed on the DL platform;

 the relations stated between the terms,

indicated by their hierarchical relative

position (e.g., metal – broader term; iron

concentrate – narrower term, iron content

and Fe-content – synonym, etc.);

 a set of rules on how to use the thesaurus in

the DL.

Thus, in order to form the interoperable

Information Retrieval Thesaurus for IST, it is

strictly recommended to provide the following

basic criteria of compiling a controlled

vocabulary:

 a set of thesaurus descriptors should be

sufficient to describe an arbitrary domain

document, particularly for the subject area

of industries or study fields; and

 the number of descriptors should not be too

large; they should contain the necessary

information for the subject area only.

Most professional guides, dictionaries, and

glossaries designed for IST are normally

systematized in alphabetical order and usually

have multiple synonyms for industry-specific

terms. In contrast, the controlled multilingual

thesaurus makes it possible to reveal the

meaning of a special term with the help of

descriptions and other concept group

correlations and to relate broader and narrower

terms.

5. Concluding Remarks

This information technology era offers great

opportunities to develop, enhance, and solve

communication issues between frontiers. This

technology is applied in various fields of human

knowledge, particularly in those related to

linguistic communication, and technical

translation in the industry area is one of them.

Machine translation systems used by translators

of any nationality and culture expand, open, and

feed the communication process for all social

sectors. In this regard, this paper considers the

translation issues faced by Kazakh translators

when dealing with the special terminology of

Developing an Online Kazakh-English-Russian Thesaurus of Industry-Specific Terminology

mining industry fields to be translated into

Russian and English. According to the study

results, it is concluded that these issues are

mainly related to the lack of a multilingual

thesaurus that allow a suitable translation –

simultaneously – in the three languages,

keeping the same semantic structure, meaning,

and function, to maintain a clear and truthful

translation process.

To make life easier in the Kazakh translation

business, it is, therefore, necessary to develop

an industry-based thesaurus or multilingual

thesaurus for a specific field of study. The

mining industry is a rapidly developing industry

whose terminology needs careful systematization

to allow quick translation from English into

Kazakh and vice versa. The creation of a

controlled-vocabulary Kazakh-English-

Russian thesaurus answers the main question of

this research: Kazakh translation issues not

having a multilingual tool to provide accurately

translated equivalents in Russian and English.

The thesaurus based on the Zthes data scheme

is a uniquely created, interoperable thesaurus

that provides equivalents for industry-specific

terms in Kazakh, English, and Russian,

respectively. Unlike other multilingual

dictionaries, the controlled multilingual

thesaurus enables the revelation of the meaning

of a term with the help of descriptions,

correlations with other concepts and their

groups, and related broader and narrower terms.

The novelty of this study is based on the prompt

and proper solution offered for translation

issues that not only helps the Kazakh scholarly

community but also others. Results have shown

the benefits of creating and using a multilingual

thesaurus to give adequate answers to specific

problems when applying certain search criteria.

These benefits are to (a) establish semantic

relations in lexical units to deal properly with

the vocabulary in the required languages, (b)

structure and systematize the terms to relate

them in the three languages in an interoperable

relation, and (c) hierarchize the term positions.

Therefore, the study of industry-specific terms

and multilingual thesauri is a promising area of

modern linguistics that unites translation,

terminology, and computational linguistics in

an interdisciplinary approach. Therefore, this

study may help to improve, develop, and create

further research in multilingual parallel

corpora, computational linguistics, and

morphological and ontological studies as well.

The controlled thesaurus of industry-specific

terms described in the present study can serve

as a model for compiling similar multilingual

dictionaries for other sectors and industries in

Kazakhstan and other countries. Furthermore, it

can be used to enrich the knowledge base for

intelligence systems, as well as build the

foundation for a Kazakh language corpus,

unifying and systematizing Kazakh industry-

specific terms in a multilingual way. Due to its

interoperability, the presented multilingual

thesaurus can easily be integrated into

international databases such as UNESCO,

NISO, and LOGOS.

Acknowledgments

This work was written within the framework of

the joint projects for a PhD thesis and a

multilingual digital thesaurus at L.

N. Gumilyov Eurasian National University and

Novosibirsk State University (the

Governmental grant for 2017–20) with the

support of Goethe University Frankfurt.

References

Ábdіrahmanov, A., & Býketov, E. (1959).

Metallýrgııa ónerkásіbі termınderіnіń

qysqasha oryssha-qazaqsha sózdіgі

[Short Russian-Kazakh dictionary of

terms of metallurgical industry]. Almaty:

Rayan.

Ábdіrahmanov, Á., & Manabaev, B. (1991). Sý

tehnıkasy termınderіnіń oryssha-

qazaqsha sózdіgі [Russian-Kazakh

dictionary of water engineering terms].

Almaty: Nauka.

Abdirasilov, E. (1999). Lıngvıstıkalyq

termınderdіń semantıkalyq qatynastary

[Semantic relations of linguistic terms].

Almaty: Nauka.

Ahmad, K., & Gillam, L. (2005). Automatic

ontology extraction from unstructured

texts. In R. Meersman, & Z. Tari (Eds.),

On the move to meaningful Internet

systems 2005: CoopIS, DOA, and

ODBASE (pp. 1330-1346). Berlin,

Heidelberg: Springer.

Aitbaiuly, O. (2013). Qazaq tіl bіlіmіnіń

termınologııasy məselelerі [The

terminological issues of Kazakh

linguistics]. Almaty: Abzal-Ai.

A. T. Bayekeyeva et al./ International Journal of Society, Culture & Language, 10(1), 2022 ISSN 2329-2210

Aitim, A. K., Satybaldiyeva, R. Z., &

Wojcik, W. (2020). The construction of

the Kazakh language thesauri in

automatic word processing system. In R.

Uskenbayeva (Ed.), Proceedings of

ICEMIS'20: 6th ACM International

Conference on Engineering & MIS 2020

(pp. 1-4). New York: ACM Press.

Akhmed-Zaki, D., Mansurova, M., Madiyeva, G.,

Kadyrbek, N., & Kyrgyzbayeva, M.

(2021). Development of the information

system for the Kazakh language

preprocessing. Cogent Engineering,

8(1), 1896418.

Aleshinskaya, E., & Albatsha, A. (2020). A

cognitive model to enhance professional

competence in computer science.

Procedia – Computer Science, 169, 326–

329.

Altenbek, G., & Sun, R. (2010). Kazakh noun

phrase extraction based on N-gram and

rules. In M. D. G. Zhou, H. Qi, & M.

Zhamg (Eds.), Proceedings of IALP

2010: 2010 International Conference on

Asian Language Processing (pp. 305–

308). Los Alamitos, CA: IEEE Computer

Society.

Ámіrbaev, M., Bektaev, Q., Bókeıhanov, R.,

Jáýtіkov, O., Orazbaev, B., & Sátbaev, M.

(1959). Oryssha-qazaqsha termınologııa

sózdіgі [Russian-Kazakh dictionary of

terminology] . Almaty: Publishing

House of the Academy of Sciences of the

Kazakh SSR.

National Information Standards Organization

(2003). Information retrieval (Z39.50):

Application service definition and

protocol specification (ANSI/NISO

Z39.50-2003). Bethesda, MD: NISO

Press.

National Information Standards Organization

(2005). Guidelines for the construction,

format and management of monolingual

controlled vocabularies (ANSI/NISO

Z39.19-2005). Bethesda, MD: NISO

Press.

Baitursynuly, A. (2009). Til – qural. [Language

as a tool]. Almaty: Sardar.

Bakaev, M., Nuǵymanov, Q., Seıdýalıev, Z.,

Ybyraev, Sh., & Ulyqbekov, O. (1962).

Oryssha-qazaqsha termınologııa sózdіgі.

Taý-ken іsterі [Russian-Kazakh

dictionary of terminology. Mining].

Almaty: Publishing House of the

Academy of Sciences of the Kazakh

SSR.

Bayekeyeva, A., Tazhibayeva, S., Shaheen, A.,

Beisenova, Z., & Mamayeva, G. (2020).

Multilingual thesaurus of industry-

specific terms as major aids for

translators. Opción, 36(27), 1864-1900.

Beisenova, Z. (2011). Otraslevaya terminologiya:

Sistemnost, tipologiya, funktsionirovaniye

[Industry-specific terminology: System,

typology, functions]. Astana: CBO and

MI.

Beisenova, Z. (2014). Intercultural approach of

professional lexicon in veterinary

medicine. London: Aitmatov Academy.

Bekbulatov, E., & Kartbayev, A. (2014). A

study of certain morphological structures

of Kazakh and their impact on the

machine translation quality. In A. Adamov

(Ed.), Proceedings of Application of

Information and Communication

Technologies: 8th IEEE International

Conference (pp. 1-5). Los Alamitos, CA:

IEEE Computer Society.

Bіrіmjanov, B., & Omarov, S. (1974). Hımııa

termınderіnіń oryssha-qazaqsha sózdіgі

[Russian-Kazakh dictionary of chemical

terms]. Almaty: KazGosNII.

Bloschchynskyi, I., Borakovskyy, L., Prihodko,

G., Novikova, T., Moroz, N., &

Kalyniuk, N. (2021). The comparative

analysis of the English and German term-

formation in the legislative documents

(based on the Schengen Border Code).

International Journal of Society, Culture

& Language, 9(3), 73-81.

Cabrė, M. (1998). Terminology: Theory,

methods and applications. Amsterdam/

Philadephia: John Benjamins Publishing

Company.

Djanabekov, K., & Djanabekova, G. (2013).

Oryssha-qazaqsha veterınarlyq sózdіk

[Russian-Kazakh veterinary dictionary].

Almaty: Sózdіk Slovar.

Encyclopedia Britannica (15

ed.). (1998).

Chicago: Encyclopedia Britannica.

Fay, A. (1920). A glossary of the mining and

mineral industry. Washington: Government

Printing Office.

Fedotov, A., Tussupov, J., Sambetbayeva, M.,

Fedotova, O., Sagnayeva, S.,

Bapanov, A., & Tazhibaeva, S. (2016).

Classification model and morphological

analysis in multilingual scientific and

educational information systems.

Developing an Online Kazakh-English-Russian Thesaurus of Industry-Specific Terminology

Journal of Theoretical and Applied

Information Technology, 86(1), 96–111.

Franco, J. (2004). The study of technical and

scientific translation: An examination of

its historical development. The Journal

of Specialized Translation, 1, 29-49.

Heidari, F., Jalilifar, A., & Salimi, A. (2020).

Developing a corpus-based word list in

pharmacy research articles: A focus on

academic culture. International Journal

of Society, Culture & Language, 8(1), 1-

15.

Hornby, A. (1995). Oxford advanced learner’s

dictionary. Oxford: Oxford University

Press.

IFLA. (2009). Guidelines for multilingual

thesauri (IFLA professional reports:

115). Retrieved from http://www.ifap.ru/

library/book411.pdf

Ilyasova, G. (2010). Oryssha-qazaqsha

termınologııalyq anyqtamalyq sózdіk

(Aqparattyq júıe salasy) [Russian-

Kazakh terminological dictionary.

Information systems]. Almaty:

Memlekettіk Tіldі Damytý Instıtýty.

Isakova, S. (2000). Qazaq tіlіndegі psıhologııa

termınderі [Terms of psychology in the

Kazakh language]. Almaty: Sózdіk

Slovar.

Joldasbekov, Ó., & Ábdіrahmanov A., (1968).

Oryssha-qazaqsha mehanızm men

mashınalardyń termınologııalyq sózdіgі

[Russian-Kazakh terminological dictionary

of mechanisms and machines]. Almaty:

Publishing House of the Academy of

Sciences of the Kazakh SSR.

Joldasbekov, Ó., & Saǵıtov M. (1994).

Teorııalyq mehanıka termınderіnіń

oryssha-qazaqsha sózdіgі [Russian-

Kazakh dictionary of terms of theoretical

mechanics]. Almaty: Nauka.

Kaidarov, A. (1993). Qazaq termınologııasyna

jańasha kózqaras [A new view on

Kazakh terminology]. Almaty: Nauka.

Kaliuly, B. (2008). Qazaq termıntanymynyń

ózektі máselelerі [Topical issues of

Kazakh terminology]. Almaty: Sózdіk

Slovar.

Kartbayev, A. (2015). Learning word alignment

models for Kazakh-English machine

translation. In V.-N. Huynh, M.

Inuiguchi, & T. Demoeux (Eds.),

Proceedings of Integrated Uncertainty in

Knowledge Modelling and Decision

Making: 4th International Symposium,

IUKM 2015 (pp. 326-335). Cham:

Springer.

Karatyshkanov, N. (1927). Pán sózderі

[Subject terms]. Almaty: Er-Daulet.

Khairova, N., Kolesnyk, A, Mamyrbayev, O.,

& Mukhsina, K. (2019). The aligned

Kazakh-Russian parallel corpus focused

on the crime theme. In V. Lytvyn, N.

Sharonova, T. Hamon, O. Cherednichenko,

N. Grabar, A. Kowalska-Styczen, & V.

Vysotska (Eds.), Proceedings of

Computational Linguistics and

Intelligent Systems: 3rd International

Conference, COLINS-2019 (pp. 116-

125). Aachen: CEUR Workshop

Proceedings.

Koyanbayev, A., & Sabirova, N. (2013). Keme

qurylysynyń sózdіgі. Oryssha-

aǵylshynsha-qazaqsha [Dictionary of

ship construction. Russian-English-

Kazakh]. Almaty: Sózdіk Slovar.

Kuandykova, A., Kartbayev A., &

Kaldybekov, T. (2014). English-Kazakh

parallel corpus for statistical machine

translation. International Journal on

Natural Language Computing, 3(3), 65-

72.

Kurmanbaiuly, S. (2014). Qazaq termınologııasy:

Zertteýler, oqýlyq, sózdіk, bıblıografııa

[Kazakh terminology: Research, manual,

dictionary, bibliography]. Almaty: Sardar.

Kurmanbaiuly, S., & Sapina, S. (2004).

Oryssha-qazaqsha, Qazaqsha-Oryssha

termınder men ataýlar sózdіgі.

Memtermınkom bekіtken termınder men

ataýlar sózdіgі [Russian-Kazakh,

Kazakh-Russian dictionary of terms.

Dictionary of terms approved by

Terminological Committee]. Almaty:

Sózdіk Slovar.

Leichik, V. (2009). Terminovedenie: Predmet,

metody, struktura [Terminology: Subject,

methods, structure]. Moscow: Librokom.

Lotte, J. (1961). Osnovy ostroeniya nauchno-

tekhnicheskoj terminologii [Fundamentals

of building scientific and technical

terminology]. Moscow: AS USSR.

Makhambet, A. (2015). Munaı men gaz oıynsha

Qazaqsha-oryssha aaǵylshynsha sózdіk

[Kazakh-Russian-English dictionary for

oil and gas]. Almaty: Asyl Sóz.

Makhambetov, O., Makazhanov, A.,

Yessenbayev, Z., Matkarimov, B.,

Sabyrgaliyev, I., & Sharafudinov, A.

(2013). Assembling the Kazakh

A. T. Bayekeyeva et al./ International Journal of Society, Culture & Language, 10(1), 2022 ISSN 2329-2210

language corpus. In D. Yarowsky, T.

Balwin, A. Korhonen, K. Livescu, & S.

Bethard (Eds.), Proceedings of EMNLP

2013: 2013 Conference on Empirical

Methods in Natural Language

Processing, (pp. 1022–1031). Seattle,

WA: Association for Computational

Linguistics.

Mansurova, M., Madiyeva, G., Aubakirov, S.,

Yermekov, Z., & Alimzhanov, Y.

(2017). Design and development of

media-corpus of the Kazakh language. In

N. Nguyen, G. Papadopoulos, P.

Jędrzejowicz, B. Trawiński, & G. Vossen

(Eds.), Proceedings of Computational

Collective Intelligence: Lecture Notes in

Computer Science, (Vol. 10449, pp. 509–

518). Cham: Springer.

Mashanov, A., Ábdіrahmanov, A., & Sadyqov, J.

(1960). Geologııa termınderіnіń

oryssha-qazaqsha sózdіgі [Russian-

Kazakh dictionary of geological terms].

Almaty: Publishing House of the

Academy of Sciences of the Kazakh

SSR.

Mashanov, A. Mýsın, A., & Aıtashev, Ǵ.

(1959). Metallýrgııa ónerkásіbі, taý-ken

іsі jáne fizıka termınderіnіń oryssha-

qazaqsha sózdіgі [Russian-Kazakh

dictionary of terms of metallurgy, mining

and physics]. Almaty: Publishing House

of the Academy of Sciences of the

Kazakh SSR.

Medeubekuly, S., Omarova, B., & Abdiyeva, R.

(2013). Baspa jjáne polıgrafııa

termınderіnіń túsіndіrme sózdіgі

[Dictionary of polygraphs terms].

Almaty: Sózdіk Slovar.

Myńbaev, K., Shynybaev, M., & Baımіrov, M.

(1983). Aýyl sharýashylyǵyn

mehanıkalandyrýdyń oryssha-qazaqsha

sózdіgі [Russian-Kazakh dictionary of

agricultural mechanization]. Almaty:

Nauka.

Niyazbek, M., & Talp, K. (2019). The Kazakh

terminology recognition system in the IT

field. IOP Conference Series: Earth and

Environmental Science, 371(5), 052028.

Omarov, E. (1923). Fızıka pán sózderі. Fızıka

[Physics subject words. Physics].

Astana: IC-Servis.

Omashuly, D. (2013). Zańnama uǵymdarynyń

tezaýrýsy [Thesaurus of legal terms].

Almaty: Sózdіk Slovar.

Oztopcu, K., Abuov, Zh., Kambarov, N., &

Azemoun, Y. (1996). Dictionary of the

Turkic languages. London and New

York: Routledge.

Qudaibergenov, R. (2009). Tehnikalyq terminder

sözdıgı [Dictionary of technical terms].

Almaty: Taimas.

Qulmanov, S. (2009). Oryssha-qazaqsha

termınologııalyq anyqtamalyq sózdіk

(Sáýlet jáne qurylys salasy) [Russian-

Kazakh terminological dictionary.

Architecture and construction]. Almaty:

Memlekettіk Tіldі Damytý Ortalyǵy.

Rakhimova, D., & Zhumanov, Z. (2017).

Complex technology of machine

translation resources extension for the

Kazakh language. Advanced Topics in

Intelligent Information and Database

Systems, Studies in Computational

Intelligence, 710, 297–307.

Reformatsky, А. (1961). Chto takoe termin i

terminologiya. Voprosy terminologii

[What is a term and terminology.

Questions of terminology]. Moscow:

Nauka.

Sambetbayeva, M. A., Fedotov, A. M., Tusupov,

J. A., Sagnayeva, S. K., Bapanov, A. A.,

Nurgulzhanova, A. N., & Yerimbetova,

A. S. (2016). Using the thesaurus to

develop it inquiry systems. Journal of

Theoretical and Applied Information

Technology, 86(1), 44-61.

Serıkbaev, D., Joldasbekov, O., Tajıbaev, S., &

Abdrahmanov, A. (1974). Rýssko-

kazahskıı termınologıcheskıı slovar po

mashınostroenııý [Russian-Kazakh

terminological dictionary on machine

building]. Almaty: Publishing House of

the Academy of Sciences of the Kazakh

SSR.

Sharipbay, A., Razakhova, B., Mukanova, A.,

Yergesh, B., & Yelibayeva, G. (2019).

Syntax parsing model of Kazakh simple

sentences. In I. Hoballah (Ed.),

Proceedings of DATA’19: Second

International Conference on Data

Science, E-Learning and Information

Systems (pp. 1–5). New York:

Association for Computer Machinery.

Superanskaya, A., Podolskaya, N., &

Vassilyeva, N. (2012). Obshchaya

terminologiya: Voprosy teorii [General

terminology: Questions of theory].

Moscow: Librokom.

Developing an Online Kazakh-English-Russian Thesaurus of Industry-Specific Terminology

Sydyqov, J., & Qabıev, F. (1993). Gıdrogeologııa

men ınjenerlіk geologııa jónіndegі

oryssha-qazaqsha termınologııalyq

sózdіk [Russian-Kazakh terminological

dictionary of hydrogeology and

engineering geology]. Almaty: Nauka.

Toksanbay, S. (2013). Poshta termınderіnіń

jáne poshta qyzmetterі salasynda jıі

qoldanylatyn sóz tіrkesterіnіń qazaqsha

oryssha sózdіgі [Russian-Kazakh

dictionary of post terms and phrases].

Almaty: Oı Sana.

Tukeyev, U., & Karibayeva, A. (2020).

Inferring the complete set of Kazakh

endings as a language resource. In M.

Hernes, K. Wojtkiewicz, & E. Szczerbicki

(Eds.), Proceedings of Advances in

Computational Collective Intelligence:

Communications in Computer and

Information Science (Vol. 1287, pp. 741–

751). Cham: Springer.

Turganbayeva, A., & Tukeyev, U. (2020). The

solution of the problem of unknown

words under neural machine translation

of the Kazakh language. Journal of

Information and Telecommunication,

5(2), 214–225.

Tursyn, Q. (2015). Mass media jáne

telekommýnıkatsııa termınderіnіń qazaqsha

-oryssha-aǵylshynsha anyqtamalyq

sózdіgі [Kazakh-Russian-English

dictionary of mass media and

telecommunication terms]. Almaty:

Qazaq Entsıklopedııasy.

Tussupov, J, Sambetbayeva, M, Fedotov, A,

Sagnayeva, S, Bapanov A,

Nurgulzhanova, A., & Yerimbetova, A.

(2016). Using the thesaurus to develop

IT inquiry systems. Journal of

Theoretical and Applied Information

Technology, 86(1), 44–61.

Yelibayeva, G., Mukanova, A., Sharipbay, A.,

Zulkhazhav, A., Yergesh, B., &

Bekmanova, G. (2019). Metalanguage

and knowledgebase for Kazakh

morphology. In S. Misra et al. (Eds.),

Proceedings of Computational Science

and Its Applications: ICCSA 2019,

Lecture Notes in Computer Science, (Vol.

11619, pp. 693-706). Cham: Springer.

Yerimbetova, A. (2016). Baılanystar

grammatıkasyn zertteý, mátіnder

relevanttylyǵyn jáne taqyrybyn anyqtaý

[Study of grammar of connections,

determination of relevance and theme of

texts]. Astana: Delta Press.

Yessenbayev, Z., Kozhirbayev, Z., &

Makazhanov, A. (2020). KazNLP: A

pipeline for automated processing of

texts written in Kazakh language. In A.

Karpov, & R. Potapova (Eds.),

Proceedings of Speech and Computer:

22nd International Conference,

SPECOM 2020 (pp. 657–666). Berlin,

Heidelberg: Springer-Verlag.