=Paper=
{{Paper
|id=Vol-2604/paper39
|storemode=property
|title=Peculiarities of Generation of Semantics of Natural Language Speech by Helping Unlimited and Context-Dependent Grammar
|pdfUrl=https://ceur-ws.org/Vol-2604/paper39.pdf
|volume=Vol-2604
|authors=Vasyl Lytvyn,Solomiya Kubinska,Andriy Berko,Tetiana Shestakevych,Lyubomyr Demkiv,Yuriy Shcherbyna
|dblpUrl=https://dblp.org/rec/conf/colins/LytvynKBSDS20
}}
==Peculiarities of Generation of Semantics of Natural Language Speech by Helping Unlimited and Context-Dependent Grammar==
https://ceur-ws.org/Vol-2604/paper39.pdf
Peculiarities of Generation of Semantics of Natural
Language Speech by Helping Unlimited and Context-
Dependent Grammar
Vasyl Lytvyn[0000-0002-9676-0180]1, Solomiya Kubinska[0000-0003-3201-635X]2, Andriy
Berko[0000-0001-6756-5661]3, Tetiana Shestakevych[0000-0002-4898-6927]4, Lyubomyr
Demkiv[0000-0002-2802-3461]5, Yuriy Shcherbyna6
1-5Lviv Polytechnic National University, Lviv, Ukraine
6Ivan Franko National University of Lviv, Lviv, Ukraine
Vasyl.V.Lytvyn@lpnu.ua1, kubinskasm@gmail.com2,
Andrii.Y.Berko@lpnu.ua3, Tetiana.V.Shestakevych@lpnu.ua4,
demkivl@gmail.com5, Shcherbyna@franko.lviv.ua6
Abstract. The article deals with the use of generative grammars in linguistic
modeling. Description of sentence syntax modeling is used to automate the
analysis and synthesis of natural-language texts.
Keywords. Sentence structure, generative grammar, computer linguistic sys-
tem.
1 Introduction
At the present stage of development, the need to develop common and specialized
linguistic systems is forcing the use of applied and computer linguistics in the field of
information technology [3-4, 7-14, 16, 22, 25-28, 32-33, 35, 43, 50-51, 53-55, 66].
Development of mathematical models of speech to provide computer linguistic sys-
tems enables the implementation of tasks of applied linguistics, such as analy-
sis/synthesis of oral/written text content, description/indexing of text content, transla-
tion of texts, creation of lexicographic databases, etc. [7-8, 10-15, 25-28, 32-33, 43,
50-51, 53-55, 66]. Linguistic analysis of textual content consists of several sequential
processes i.e. grapheme, morphological, syntactic, and semantic analysis [2-5, 9-10,
16-23, 28-30, 34]. For each of these stages, the corresponding models and algorithms
are created [2-5, 9-10, 15-21, 44-49, 56-64]. An effective tool of linguistic modeling
at the syntactic and semantic level of language is the main part of combinatorial lin-
guistics - the theory of generative grammar, the beginning of which is based on the
works of the American linguist N. Chomsky [16-20, 45-48, 56-64]. He used the tech-
nique of formal analysis of the grammatical structure of phrases to distinguish syntac-
tic structure (constituents) as the basic scheme of a phrase, regardless of its meaning
[16]. The ideas of N. Chomsky were developed by Soviet linguist A. V. Gladkyy [18 -
Copyright © 2020 for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
20], applying the concept of dependency trees and systems of components for model-
ing syntactic language level [30, 50]. He proposed a method of syntax modeling using
syntactic groups that distinguish word components as units of constructing a depend-
ency tree, such a representation combines the advantages of the method of direct con-
stituents and dependency trees [4-5, 50].
Advantages of modelling using generative grammars are the ability to describe not
only the syntactic level of language (rules for the formation of sentences from word
forms) [12-14, 18-20, 48, 51], but also morpheme (rules for the formation of word
forms from morphs) [9-10, 23, 38-41, 55], and semantic (rules of formation of mean-
ingful sentences and texts) [2, 29-30, 47, 49, 56]. It is used for automation of word-
change / word-formation processes, rubric or definition of keywords and formation of
text content digest [7-8, 10-11, 23-28, 43, 66]. For example, when using automatic
morphological synthesis, a computer linguistic system generates the necessary word
forms based on the requirements for word forms and morpheme databases [32].
2 Connection of the Highlighted Issue to Important Scientific
and Practical Work
Based on the importance of providing automatic processing of textual content in
modern information tools (for example, information retrieval systems, machine trans-
lation, semantic, statistical, optical and acoustic analysis and synthesis of language,
automated editing, extraction of knowledge of textual content, abstracting and anno-
tating , indexing of textual content, educational and didactic, management of linguis-
tic corpora, tools for compiling dictionaries of various types etc.), experts are inten-
sively looking for new models, methods of their description and methods of automatic
processing of textual content [7-8, 10-11, 23-28, 43, 66]. One such method is to de-
velop general principles for the construction of lexicographic systems of syntactic
type and to build on these principles these systems of textual content processing for
specific languages [7-8, 10-11, 23-28, 43, 66].
Studies of linguists in the field of morphology, morphonology, structural linguis-
tics have identified different structures for describing word forms [7-8, 10-15, 25-28,
32-33, 43, 50-51, 53-55, 66]. With the beginning of the development of the theory of
generative grammars, linguists have focused not only on the description of ready
word forms, but also on the processes of their synthesis [38]. Functional studies of
linguists in Ukrainian are fruitful [2-3, 6, 12-14, 22-24, 28, 30, 32-33, 39, 42-43, 51-
55], in particular, theoretical problems of morphological description [ 9-10, 23, 38-41,
55], questions of classification of morphemic and word-forming structure of deriva-
tives of Ukrainian language [23], regularities of combinatorics of affixes [23, 55],
modeling of word-formation mechanism of modern Ukrainian language in dictionar-
ies of integral type [23, 38- 39], the principles of the internal organization of the word
[23, 55], as well as the questions of the structural organization of distinct verbs and
suffixes of eminative value [23, 38, 55], problems of word-forming motivation in the
process of derivatives formation [23], regularities of realization of morphonological
phenomena in Ukrainian word-formation [23, 39, 55], morphonological modifications
in the process of verb-word change [23, 38, 55], morphonological processes in word-
translation and word-formation of adjectives of modern Ukrainian literary language
[23, 38-39], analysis and processing of textual content [7-8, 10-14, 22, 25-28, 30, 32-
33, 43, 55, 66] etc.
Such a dynamic approach of modern linguistics in the analysis of the morphologi-
cal level of the language, with the researcher's focus on the development of morpho-
logical rules, makes it possible to effectively apply the results of theoretical research
in practice - for the construction of computer linguistic systems for processing textual
content for various purposes [7-8, 67-74]. One of the first attempts to apply the theory
of generative grammars to linguistic modeling is A.V. Gladkyy and I.A. Melchuk [18-
20]. Developments by N. Chomsky [16-20, 45-48, 56-64] and A.V. [18-20], the study
of M. Gross and A. Lanten [21], A.V. Anisimova [2-3], Yu.D. Apresian [4-5], N.C.
Bilgaeva [9], I.A. Volkova and T.V. Rudenko [15], E.I. Bolshakova, ES Klyshynskyi,
DV Lande, A.A. Noskova, OV Peskova, and E.V. Yagunova [10-11, 26-27], A.S.
Gerasimova [17], B.K. Martynenko [29], A.E. Pentus and M.R. Pentus [34], E.V.
Popova [35], V.S. Fomicheva [44] are applicable to the development of such textual
content processing tools as information retrieval systems, machine translation sys-
tems, textual content annotation, morphological, syntactic and semantic analysis of
textual content, educational and didactic textual content processing systems, to special
systems of linguistic content etc. [7-8, 10-14, 22, 25-28, 30, 32-33, 43, 55, 66].
3 Analysis of scientific results
Grammar has the following important in the linguistic aspect. We will interpret termi-
nal symbols as wordforms (some natural language), auxiliary symbols - as syntactic
categories (for example, V is verb, S is noun, A is adjective, Ṽ is group of verbs, S is
noun group), initial symbol – as (sentences), and terminal strings, that are deduced -
as correct sentences of the given language. Then the derivation of a sentence is natu-
rally interpreted as its syntactic structure, presented in terms of direct constituents.
Let's explain the examples.
1. Весела посмішка твого сина наповнює мене безмежним щастям [12-14, 51].
2. In seinem bedeutendsten Werk zeigt er die bunte welt des ukrainischen Dorfes in
ihrem einmaligen Reiz [31].
Constructing a grammar G1 that will generate phrases of the corresponding language
(Ukrainian, English or German), syntactically same and very simple [1, 6, 10-14, 22,
24, 28, 31, 36-42, 49, 51-55, 65] . Let us write out only the scheme of this grammar;
its terminal symbols are the word forms of the corresponding language, and the auxil-
iary dictionary contains the above syntactic categories. The symbols of these catego-
ries are provided with indexes corresponding to their morphological features, for ex-
ample Sж ,oд, р . The initial character is indicated by R.
Diagram of grammar G1. The contents of the designations used G1 are explained
after the table 1.
Table 1. Rules for the formulation of sentences in Ukrainian
The name
№ Rule
of the rule
Choice of
I. R # S x, y ,н, w Vy ,тепер, w #
structure R .
S x, y , z ,3 S x, y , z ,3 S x, y, р, w
1) ;
S x, y , z ,3 Ax, y , z S x, y , z ,3
2) ;
K1S x, y , z , w K 2 K1S xзайм
, y, z,w K2 K1 – a symbol other than a
3) , де
Ax , y , z
K 2 – a character other than an index character
Deploying a symbol , а
II. Nominal z р . Symbols K1 and K 2 are contextual constraints. The substan-
Group tive meaning of their introduction to this rule is that the principal member
of a nominal group should not be implemented by a personal pronoun if
it is preceded by a definition expressed by an agreed adjective, or if it is
followed by a nominal group in the generic case, for example, the impos-
sibility of a new self or tenderness. In poetic language, such combina-
tions suggest;
S x, y , z ,3 S x, y , z
4) .
Vy ,тепер, w Vy ,тепер, w S x, y, зн, w S x, y,ор, w
1) ;
Deployment Vy ,тепер, w Vy ,тепер, w S x, y,ор, w S x, y, зн, w
2) ;
III. verbal
groups Vy ,тепер, w Vy ,тепер, w S x, y, зн, w
3) ;
Vy ,тепер, w Vy ,тепер, w S x, y,ор, w
4) .
Sч, у , z син y , z ,...
1) ;
Sж, у , z посмiшка y , z ,...
2) ;
Sсер, у , z щастя y , z ,...
Realization 3)
IV.
syntactic S хзайм
,од, z ,1 яz
categories 4) ;
word forms S займ тиz
5) х,од, z ,2 ;
Ах, у , z веселийх, y , z , безмежнийх, y , z , мiйх, y , z , твiйх, y , z ,...
6) ;
Vу ,тепер, w наповнити y ,тепер, w ,...
7)
Each line in this diagram is not a single rule, but a abbreviation entry of several rules.
Thus, line II.1 forms 648 rules for forming phrases in Ukrainian [6, 12-14, 24, 42, 51,
52, 55]:
Sч,од,н,3 Sч,од,н,3 Sч,од, р,1 ; Sч,од, р ,3 Sч,од, р ,3 Sч,од, р ,1 ; …; Sсер , мн, м,3 Sсер , мн, м,3 Sсер, мн, род,3 ,
where the abbreviation ч is masculine, од is singular, н is a nominative distinguisher,
р is a generic distinguisher, сер is an average genus, мн is a plurality, м is a abla-
tive, 1 is the first person of the noun, 3 is the third person of the noun. The same
method of reduction is used in the following examples. However, for the sake of sim-
plicity, we will refer to the lines of such abbreviated entries as rules (Table 2). Rule
IV does not take into account the matching A of the noun of the creature S in the
аccusative case. Designation: # - the symbol of the boundary of the sentence, which
is terminal (in the text, the left border is capitalized in the first letter of the word, and
the right - in a dot); x, y, z, w - characteristics of word forms corresponding to the
type, number, case, person, for example, веселийж ,од,н весела . An example of a
grammar G1 derivation for generating a Ukrainian sentence is shown in fig. 1.
1. R
2.(I) # S ж ,од ,н ,3 Vод,тепер ,3 #
3.(III.1) # S ж ,oд,н ,3 Vод, тепер ,3 Sч ,од, зн ,1 Sсер ,од ,ор ,3 #
# S ж ,од, н,3 Sч ,од, р ,3 Vод, тепер ,3 Sч ,од, зн ,1 Sсер ,од ,ор ,3 #
4.(II.1)
5.(II.2) # Аж ,од,н S ж ,од ,н ,3 Sч ,од , р ,3 Vод,тепер ,3 Sч ,од , зн ,1 Sсер ,од ,ор ,3 #
6.(II.2) # Аж ,од,н S ж ,од ,н ,3 Ач ,од, р Sч ,од , р ,3 Vод, тепер ,3 Sч ,од , зн ,1 Sсер ,од ,ор ,3 #
7.(II.2) # Аж ,од ,н S ж ,од ,н ,3 Ач ,од , р Sч ,од , р ,3 Vод, тепер ,3 Sч ,од , зн ,1 Асер ,од ,ор Sсер ,од ,ор ,3 #
8-9 ..............................................................................................................................
10.(II.4) # Аж ,од ,н S ж ,од ,н Ач ,од , р Sч ,од, р Vод,тепер ,3 Sч ,од, зн ,1 Асер ,од ,ор Sсер ,од ,ор #
11.(II.3) # Аж ,од ,н S ж ,од,н Ач ,од, р Sч ,од , р Vод,тепер ,3 Sчзайм
,од , зн ,1
Асер ,од,ор Sсер ,од,ор #
12-18 ............................................................................................................................
IV.6 IV.2 IV.6 IV.1 IV.7 IV.4 IV.6 IV.3
весела посмiшка твого сина наповнює мене безмежним щастям
# #
Fig. 1. Example of phrase structure grammar (type 0) for generating a Ukrainian sentence
Grammar can give rise to other phrases (which are not necessarily meaningful), for
example: я наповнюю тебе щастям, веселе безмежне моє щастя наповнює
тобою твоїй посмішці щастя твоєї посмішки щастя, etc. Grammar G1 generates
infinitely many different phrases (as opposed to grammar G0), since its composition
includes the so-called cyclic rules (II.1 and II.2). The peculiarity of such a rule is that
the result of its application contains the occurrence of its left, so that it can always be
applied to its own result, which leads to an infinite number of phrases: yes, along with
a group of весела посмішка you can get a весела весела посмішка, further весела
весела весела посмішка, etc., so, the adjective весела can be repeated as many times
as you like. This raises the question of the infinite number of phrases in natural lan-
guage, in relation to which we note that at any given moment the number of words of
any natural language is finite. In addition, the maximum length of phrases occurring
in a language is practically limited: it is unlikely that people use phrases more than,
say, 1000 words. It follows that the number of phrases in natural language should be
finite. But it is not possible to specify the longest phrase: whichever phrase is not
suggested, we can always extend it by adding, for example, another homogeneous
term or a contract sentence of which. In natural language, there are fundamental pos-
sibilities for constructing as many long phrases as possible, that is, potentially real
phrases of any length, although in practice large phrases do not use them. This poten-
tial unlimited length of phrases cannot be ignored by formal grammarians, since their
task is to model the fundamental possibilities of natural language. If the lengths of
grammar-generated phrases are infinite, then the set of all these phrases is infinite.
For German, record II.1 forms 288 rules: Sm,einz ,nom,3 Sm,einz ,nom,3 Sm,einz , gen,1 ;
Sm,einz , gen,3 Sm,einz , gen,3 Sm,einz , gen,1 ; …; Sn, plur ,akk ,3 Sn, plur ,akk ,3 Sn, plur ,akk ,3 , where m is
Maskulinum (masculine), einz is Einzahl (singular), nom is Nominativ (nominal), gen
is Genitiv (genetive), n is Neutrum (neuter), akk is Akkusativ (accusative), plur is
Plural (plural), 1 is erste Person Substantiv (first person of the noun), 3 is dritte Per-
son Substantiv (third person of the noun) [12-13, 31, 36-37, 41, 49]. In the table 2 sets
out the rules for formulating sentences in German.
Table 2. Rules for the formulation of sentences in German
The name
№ Rule
of the rule
Choice of R # S x, y ,nom, w Vy , pr , w #
1) ;
I. structure
R R # S x, y ,dat , w Vy , pr , w #
2) .
S x, y , z ,3 S x, y , z ,3 S x, y, gen, w
1) ;
S x, y , z ,3 Ax, y , z S x, y , z ,3
2) ;
K1S x, y , z , w K 2 K1S xpron
, y, z,w K2 K1 — a symbol other than a sym-
3) , де
bol, and
K 2 — a character other than an index z gen . Symbols are
Deploying a
II. Nominal K
contextual constraints. The 1 and 2 substantive meaning of their
K
Group introduction to this rule is that the principal member of the nominative
group should not be implemented by a personal pronoun if it is preceded
by a definition expressed by an agreed adjective, or if it is followed by
іменна група в a generic case, such as the impossibility of neu ich (new)
or er Zärtlichkeit (he of tenderness). In poetic language, such combina-
tions suggest;
S x, y , z ,3 S x, y , z
4) ;
The name
№ Rule
of the rule
S x, y , z ,3 S x, y , z ,3 S x, y,akk , w
5) ;
S x, y , z ,3 S x, y , z ,3 S x, y,dat , w
6)
Vy , pr , w Vy , pr , w S x, y,akk , w S x, y, gen, w
1) ;
Vy , pr , w Vy , pr , w S x, y, gen, w S x, y,akk , w
2) ;
Vy , pr , w Vy , pr , w S x, y,akk , w
3) ;
Vy , pr , w Vy , pr , w S x, y,akk , w S x, y, gen, w S x, y,dat , w
4) ;
Deployment Vy , pr , w Vy , pr , w S x, y,akk , w S x, y,dat , w
5) ;
III. verbal
groups Vy , pr , w Vy , pr , w S x, y,dat , w S x, y,akk , w
6) ;
Vy , pr , w Vy , pr ,w S x, y,dat ,w S x, y,akk ,w S x, y,dat ,w
7) ;
Vy , pr , w Vy , pr ,w S x, y,dat ,w S x, y,dat ,w S x, y,akk ,w
8) ;
Vy , pr , w Vy , pr ,w S x, y,akk ,w S x, y,dat ,w S x, y,dat ,w
9) ;
Vy , pr , w Vy , pr , w S x, y,nom,w
10) ;
Sm, у , z Reiz y , z ,...
1) (де der Reiz – attractiveness);
S f , у , z Welt y , z ,...
2) (де die Welt – world);
Sn, у , z Werk y , z , Dorf y , z ,...
3) (where das Werk is work, das Dorf is a
village);
Realization
syntactic ,einz , z ,1 erz
S хpron
IV. 4) (де er – he);
categories
, plur , z ,3 siez
S хpron
word forms 5) (де sie – they);
6)
Ах, у , z seinх, y , z , ihrх, y , z , bedeutend х, y , z , buntх, y , z , ukrainischх, y , z , einmaling х, y , z ,...
(where sein – my, ihr - theirs, bedeutend - important, bunt - colorful,
ukrainian - ukrainian, einmalig - unique);
V zeigeny , pr , w ,...
7) у , pr , w (де zeigen – show).
An example of grammar output for generating a German sentence is shown in fig. 2.
1. R
2.(I.2) # S n ,einz ,dat ,3 Vein , pr ,3 #
3.(III.10)# S n ,einz ,dat ,3 Veinz , pr ,3 S m ,einz ,nom ,3 #
4.(II.5) # S n ,einz ,dat ,3 Veinz , pr ,3 S m ,einz ,nom ,3 S f ,einz ,akk ,3 #
5.(II.6) # S n ,einz ,dat ,3 Veinz , pr ,3 S m ,einz ,nom ,3 S f ,einz ,akk ,3 #
S n ,einz ,dat ,3
6.(II.1) # S n ,einz ,dat ,3 Veinz , pr ,3 S m ,einz ,nom ,3 S f ,einz ,akk ,3 S n ,einz , gen ,3 S n ,einz ,dat ,3 #
7.(II.2) # А S n ,einz ,dat ,3 Veinz , pr ,3 S m ,einz ,nom ,3 S f ,einz ,akk ,3 S n ,einz , gen ,3 S n ,einz ,dat ,3 #
n ,einz , dat
8.(II.2) # А Аn ,einz ,datS n ,einz ,dat ,3 Veinz , pr ,3 S m ,einz ,nom ,3 S f ,einz ,akk ,3 S n ,einz , gen ,3 S n ,einz ,dat ,3 #
n ,einz , dat
9.(II.2) # А Аn ,einz ,datS n ,einz ,dat ,3 Veinz , pr ,3 S m ,einz ,nom ,3 Аf ,einz ,akkS f ,einz ,akk ,3 S n ,einz , gen ,3 S n ,einz ,dat ,3 #
n ,einz , dat
10.(II.2) # А Аn ,einz ,dat S n ,einz ,dat ,3 Veinz , pr ,3 S m ,einz ,nom ,3 Аf ,einz ,akkS f ,einz ,akk ,3Аn ,einz , genS n ,einz , gen ,3 S n ,einz ,dat ,3 #
n ,einz , dat
11.(II.2) # А
n ,einz , dat Аn ,einz , dat S n ,einz , dat ,3 Veinz , pr ,3 S m ,einz , nom ,3 А f ,einz , akkS f ,einz , akk ,3Аn ,einz , genS n , einz , gen ,3 Аm ,einz , dat S n , einz , dat ,3
#
12.(II.2) # А Аn ,einz ,dat S n ,einz ,dat ,3 Veinz , pr ,3 S m ,einz ,nom ,3 Аf ,einz ,akkS f ,einz ,akk ,3Аn ,einz , genS n ,einz , gen ,3 Аm ,einz ,datАm ,einz ,datS n ,einz ,dat ,3#
n ,einz , dat
13.(II.4) # А
n ,einz , dat Аn ,einz , dat
S n ,einz ,dat Veinz , pr ,3 S m ,einz ,nom ,3 Аf ,einz ,akkS f ,einz ,akk ,3Аn ,einz , genS n ,einz , gen ,3 Аm ,einz ,datАm ,einz ,datS n ,einz ,dat ,3#
14-15...............................................................................................................................................
А
16.(II.4) Аn ,einz ,dat n ,einz , dat S n ,einz , dat
# Veinz , pr ,3 S m ,einz ,nom ,3 Аf ,einz ,akk S f ,einz ,akk Аn ,einz , gen S n ,einz , gen Аm ,einz ,dat Аm ,einz ,dat S n ,einz ,dat #
17.(II.3) # Аn ,einz , dat Аn ,einz , dat S n ,einz , dat ,einz , nom ,3 А f ,einz , akk S f ,einz , akk Аn ,einz , gen S n ,einz , gen Аm ,einz , dat Аm ,einz , dat S n ,einz , dat
Veinz , pr ,3 S mpron #
18-28 ............................................................................................................................................
# IV.6 IV.6 IV.3 IV.7 IV.4 IV.6 IV.2 IV.6 IV.3 IV.6 IV.6 IV.1 #
In seinem bedeutensten Werk zeigen er die bunte Welt des ukrainischen Dorfes in ihrem einmaligen Reiz
Fig. 2. An example of a phrase structure grammar (type 0) for generating a German sentence
Let's return to fig. 1, where each step of the output consists in the deployment of one
of the characters of the previous chain (for example, in the transition from 2 to 3
chains the symbol Vод,тепер,3 is expanded in 3 characters - Vод,тепер ,3 Sч ,од, зн ,1 Sсер ,од,ор ,3 ),
or in its replacement by another (for example, in the transition from 10 to 11,
Sч ,од , зн ,1 займ
the symbol is replaced by Sч,од, зн,1 ) , the other characters are overwritten
unchanged (wildcard rules). Expandable, replaceable, or rewritable characters are
ancestors, and characters that we get from deployment, replacement, or rewriting are
their descendants (descendants of descendants are also descendants). We connect the
ancestors with the lineages with their immediate descendants. Then we get the com-
ponent tree, or the syntactic structure of the phrase in terms of immediate components
(type 1). To illustrate this, let more clearly eliminate the scheme in Fig. 1 are all de-
scendant characters that rewrite without modification (for example, Sч ,од, зн ,1 in chains
4-10) and combine the same steps 4-7 (Fig. 3).
1. R
2. # S ж ,од, н ,3 Vод,тепер ,3 #
3. Vод ,тепер ,3 Sч ,од , зн ,1 Sсер ,од,ор ,3
4. S ж ,од,н ,3 Sч ,од, р ,3
5. Аж ,од,н S ж ,од ,н ,3 Ач ,од , р Sч ,од, р ,3 Асер ,од ,ор Sсер ,од,ор ,3
6. S ж ,од ,н Sч ,од , р Sчзайм Sсер ,од ,ор
,од , зн ,1
7. # весела посмiшка твого сина наповнює мене безмежним щастям #
Fig. 3. Example of context-dependent grammar of immediate components (type 1)
Context-free grammars are a special case of grammars of direct components (an ex-
ample of using context in G1 is rule II.3). Their value is due to the following circum-
stances:
rejection of the context (there is exactly one character in the left side of the rule)
makes the grammar structure easier and easier to study;
although in natural languages the replacement of one unit by another is permissi-
ble in certain contexts, it is advisable to investigate the possibility of describing the
language without distracting from that fact.
This differentiates between contextual use cases and non-contextual cases. Of particu-
lar interest is the study of situations where context is meaningful, but formally taken
into account by context-free rules, that is, they are not considered as context (new
categories are introduced into the grammar). Thus, in grammar G1 context-dependent
rule II.3 is eliminated (alg. 1).
Algorithm 3. Conversion of context-dependent grammar into context-free grammar.
Step 1. New characters Sx, y ,z are introduced into the auxiliary dictionary to inter-
pret non-noun groups, as opposed to characters Sx, y ,z that indicate arbitrary noun
groups.
Step 2. Regulation II.3 is replaced by two new rules: S x , y , z , w S x , y ,w and
займ
Sx , y ,z ,3 Sx , y ,z .
Step 3. In rules II.1, II.2 and II.4, all occurrences of characters S x , y ,z ,3 are replaced
by characters Sx , y ,z ,w . When you deploy an arbitrary namespace S x , y ,z ,w to a structure
A S or S S р to make sure that a personal pronoun such as I, you, you, he, she, it,
that cannot have definitions (A or Sp: новий я or ми посмішки) appears in the design
header. This is determined in different ways.
займ
1. Personal pronouns are considered as personal class nouns - S and are treated as
noun groups alongside ordinary nouns. It is only allowed to move from a noun
S
займ
group S to S the condition that it has not previously separated from itself to the
left or right (rules II.1 and II.2), that is, if there is no adjective to the left of the
symbol S and no noun group to the right in the case. This condition is taken into
account in Regulation II.3.
2. The pronoun is considered a special class of nouns, but along with the category ar-
bitrary noun group S enter the category of proper noun (non-noun) group S , and
the symbol S during the output - before its deployment - must be replaced by ei-
займ
ther a symbol S (which can not expand further), or to the symbol S (which is
expanded in the usual way); A and S р only appear with S , but S cannot become
a pronoun.
3. Pronouns do not consider nouns and use a symbol M for them. Then, most gram-
mar rules of G1 are duplicated, for example, with rule I they introduce rule I':
R М од,наз ,wVод,тепер ,w ; along with Regulation III.3 - Regulation III.3 ':
Vy ,тепер,w Vy ,тепер,w М х, y, зн,w etc. The received grammar will be context-free.
The example above shows that in natural languages situations where context-
dependent phenomena are described and as context-independent are possible, that is,
in terms of context-free grammars. This complicates the description, introducing new
categories and rules. Not every context-dependent is replaced by equivalent context-
free grammar. It is known that there are direct component languages that are not con-
text-free languages, such languages a b a aba, aabbaa, or a b c . Almost all
n n n n n n
examples of non-context-free languages are abstract in nature and have no interpreta-
tion in natural languages.
However, for any context-free grammar you can construct an equivalent binary
context-free grammar. For example, the context-free grammar shown in Fig. 2, con-
verted into binary by replacing rules III.1 and III.2 with the following new rules:
III. 1') Vy ,тепер ,w Vy ,тепер ,w S x, y,ор ,w ; III. 1'') Vy ,тепер , w Vy ,тепер , w S x, y, зн,w ;
1 1
III. 2') Vy ,тепер ,w Vy ,тепер ,w S x, y, зн ,w ; III. 2'') Vy ,тепер ,w Vy ,тепер ,w S x, y,ор ,w .
2 2
It is still necessary to replace rule I by rule I ': R S x , y ,н,wVy ,тепер ,w ; thus eliminating
boundary characters (generally, in context-free grammar, boundary symbols are not
formally required, whereas in grammars of direct constituents having context-
dependent rules, boundary characters may be required as context (rule II.3 in G1 ).
There is a restriction (not more than two characters in the right-hand side of the rules)
can be overlaid on arbitrary grammars of direct components, formulating it somewhat
differently: each rule has the form of Z1CZ 2 Z1WZ 2 , where W of one or two char-
acters. For any grammar of direct constituents, one can construct an equivalent binary
grammar of direct constituents (Fig. 4).
1. R
2. S ж ,од ,н ,3 Vод,тепер ,3
3. Vод1 ,тепер ,3 Sсер ,од ,ор ,3
4. Vод,тепер ,3 Sч ,од, зн ,1
S ж ,од, н,3 Sч ,од , р ,3
5.
Аж ,од ,н S ж ,од ,н ,3 Ач ,од , р Sч ,од , р ,3 Асер ,од,ор Sсер ,од ,ор ,3
6.
S ж ,од,н Sч ,од , р Sчзайм Sсер ,од,ор
7. , од , зн ,1
8. весела посмiшка твого сина наповнює мене безмежним щастям
Fig. 4. Example of context-free grammar (type 2)
The peculiarity of regular grammars is a specific form of output. Let's build for exam-
ple regular grammar G2 , that is, the generation of sentences of the type Весела
посмішка наповнює безмежним щастям (simplified version of the sentence in Fig.
1). Diagram of grammar G2 .
R S x, y , н, w Sсер, y ,ор щастясер, y ,орVy ,3
1) 5)
S x, у , z веселаx, y , z S x, у , z S ж , y ,н поcмiшкаж , y ,н
2) 6)
S x, у , z безмежнийx, y , z S x, у , z Sсер , y ,ор щастясер , y ,ор
3) 7)
S поcмiшкаж, y ,нVy ,3 V наповнити y ,3 S x, у,op
4) ж, y ,н 8) у ,3
The given sentence will have the following interference in this grammar: there are
R
(1) S ж ,oд ,н
(2) весела S ж ,од ,н
(4) весела посмішка Voд,3
(8) весела посмішка наповнює Sсер ,од , зн
(3) весела посмішка наповнює безмежним Sсер ,од , зн
(7) весела посмішка наповнює безмежним щастям.
Each intermediate chain contains exactly one auxiliary symbol in the last position.
The sentence is generated from left to right: at each step, a specific wordform is dis-
played, followed by an auxiliary symbol indicating which construction should follow
this wordform. A wordform is then issued that begins or is contained in this construc-
tion, followed by an auxiliary symbol of the next construction, and so on. Regular
grammar implies that it follows a given word form, with the prediction depth being
one adjacent symbol; each regular choice is entirely conditioned by one previous
choice. It should be noted that it is impossible to derive a natural representation of the
structure of the immediate components of that sentence (as it was done for context-
dependent and context-free grammar) from the derivation of a sentence in regular
grammar. That is, regular grammars give some structure to constituents, however,
these constituents are usually purely formal in nature and are not amenable to natural
interpretation (Fig. 5).
R
S ж ,oд ,н
весела S ж ,од, н
посмiшка Vод ,3
наповнює Sсер ,од ,ор
безмежним Sсер ,од ,ор
весела посмiшка наповнює безмежним щастям
Fig. 5. Example of regular grammar (type 3)
Incorrectly split the sentence into two components - весела, etc., as well as attributing
the categories to the resulting component. In the sentence Посмішка наповнює мене
щастям the result would be even worse: the combination of мене щастям is a com-
ponent. This sentence is not generated by grammar G2 , but it is easy to supplement it
(by introducing two rules). The interpretation of output in regular grammars is point-
less. They use a different interpretation of regular output: as a sequence of predictions
and their implementations. There are context-free languages that are not generated by
n n
regular grammars. An example is the language that consists of view chains a b .
4 Conclusions
The article discusses known methods and approaches of addressing the automatic
processing of textual content and highlights the shortcomings and benefits of existing
approaches and results in the syntactic aspects of computational linguistics. The gen-
eral conceptual principles of modeling of word-exchange processes in the formation
of text arrays on the example of Ukrainian and German sentences were formed, then,
by proposing syntactic models and word-classifications of the lexical composition of
Ukrainian and German sentences, the lexicographic rules of syntactic type for auto-
mated processing were developed. The application of the technique allows to achieve
higher reliability indicators in comparison with the known analogues, as well as
demonstrates high efficiency in applied applications in the construction of new infor-
mation technologies of lexicography and the study of the word-exchange effects of
natural languages. The work has practical value because the proposed models and
rules make it possible to effectively organize the process of creating lexicographic
systems for processing syntactic textual content.
References
1. Angliyskaya grammatika v dostupnom izlozhenii. In: http://real-
english.ru/crash/lesson3.htm, last accessed 2019/11/21.
2. Anisimov, A.V., Marchenko, O.O., Nykonenko, A.O.: Alhorytmichna modelʹ asotsiatyv-
no-semantychnoho kontekstnoho analizu tekstiv pryrodnoyu movoyu. In: Probl.
Prohramuv, 2-3, 379-384. (2008)
3. Anisimov, A.V.: Komp'yuternaya lingvistika dlya vsekh: mify, algoritmy, yazyk. Dumka,
Kyiv, Ukraine (1991)
4. Apresyan, Y.D.: Idei i metody sovremennoy strukturnoy lingvistiki. Prosveshcheniye,
Moscow (1966)
5. Apresyan, Y.D.: Neposredstvenno sostavlyayushchikh metod. In:
http://tapemark.narod.ru/les/332a.html, last accessed 2019/11/21.
6. Bahmut, A.Y.: Poryadok sliv. In: Ukrayinsʹka mova: Entsykl, 3, 675-676. (2007)
7. Vysotska, V., Fernandes, V.B., Emmerich, M.: Web content support method in electronic
business systems. In: CEUR Workshop Proceedings, Vol-2136, 20-41 (2018)
8. Lytvyn, V., Vysotska, V.: Designing architecture of electronic content commerce system.
In: Computer Science and Information Technologies, Proc. of the X-th Int. Conf.
CSIT’2015, 115-119 (2015)
9. Bil'gayeva, N.T.: Teoriya algoritmov, formal'nykh yazykov, grammatik i avtomatov.
VSGTU, Ulan-Ude (2000)
10. Bolshakova, Y.I., Klyshinskiy, E.S., Lande, D.V., Noskov, A.A., Peskova, O.V., Yaguno-
va, Ye.V.: Avtomaticheskaya obrabotka tekstov na yestestvennom yazyke i komp'yuterna-
ya lingvistika. MIEM, Moscow (2011)
11. Lytvyn, V., Vysotska, V., Burov, Y., Veres, O., Rishnyak, I.: The Contextual Search
Method Based on Domain Thesaurus. In: Advances in Intelligent Systems and Computing,
689, 310-319 (2018)
12. Su, J., Vysotska, V., Sachenko, A., Lytvyn, V., Burov, Y.: Information resources pro-
cessing using linguistic analysis of textual content. In: Intelligent Data Acquisition and
Advanced Computing Systems Technology and Applications, Romania, 573-578, (2017)
13. Lytvyn, V., Sharonova, N., Hamon, T., Vysotska, V., Grabar, N., Kowalska-Styczen, A.:
Computational linguistics and intelligent systems. In: CEUR Workshop Proceedings, Vol-
2136 (2018)
14. Lytvyn, V., Vysotska, V., Dosyn, D., Burov, Y.: Method for ontology content and struc-
ture optimization, provided by a weighted conceptual graph, Webology, 15(2), pp. 66-85
(2018)
15. Volkova, I.A., Rudenko ,T.V.: Formal'nyye grammatiki i yazyki. Elementy teorii trans-
lyatsii. In: Izdatel'skiy otdel fakul'teta vychisli-tel'noy matematiki i kibernetiki MGU im.
M.V.Lomonosova, (1999)
16. Hakman, O.V.: Heneratyvno-transformatsiyna linhvistyka N. Khomsʹkoho yak vyra-
zhennya yoho linhvistychnoyi filosofiyi. In: Mulʹtyversum. Filosofsʹkyy alʹma-nakh, 45,
98-114. (2005)
17. Gerasimov, A.S.: Lektsii po teorii formal'nykh yazykov. In: http://gas-
teach.narod.ru/au/tfl/tfl01.pdf, last accessed 2019/11/21.
18. Gladkyy, A.V.: Sintaksicheskiye struktury yestestvennogo yazyka v avtomatizirovan-nykh
sistemakh obshcheniya. Nauka, Moscow (1985)
19. Gladkyy, A.V. Mel’chuk, I. A.: Elementy matematicheskoy lingvistiki. In: Nauka, Mos-
cow (1969)
20. Gladkyy, A.V.: Formal’nyye grammatiki i yazyki. In: Nauka, Moscow (1973)
21. Gross, M., Lanten, A.: Teoriya formal'nykh Grammatik. Mir, Moscow (1971)
22. Darchuk, N.P.: Komp’yuterna linhvistyka (avtomatychne opratsyuvannya tekstu). In: Ky-
yivs’kyy universytet VPTS, Kyiv, Ukraine (2008)
23. Demeshko, I.: Typolohiya morfonolohichnykh modeley u viddiyeslivnomu slovotvorenni
suchasnoyi ukrayins’koyi movy. In: Zbirnyk naukovykh prats’ Linhvistychni studiyi, 19,
162-167. (2009)
24. Zubkov, M.: Ukrayins’ka mova: Universal’nyy dovidnyk. In: VD Shkola, Kyiv, Ukraine
(2004)
25. Gozhyj, A., Kalinina, I., Vysotska, V., Gozhyj, V.: The method of web-resources man-
agement under conditions of uncertainty based on fuzzy logic, 2018 IEEE 13th Interna-
tional Scientific and Technical Conference on Computer Sciences and Information Tech-
nologies, CSIT 2018 – Proceedings 1, 343-346 (2018)
26. Gozhyj, A., Vysotska, V., Yevseyeva, I., Kalinina, I., Gozhyj, V.: Web Resources Man-
agement Method Based on Intelligent Technologies, Advances in Intelligent Systems and
Computing, 871, 206-221 (2019)
27. Vysotska, V., Chyrun, L.: Analysis features of information resources processing. In: Com-
puter Science and Information Technologies, Proc. of the Int. Conf. CSIT, 124-128 (2015)
28. Lyubchenko, T.P.: Leksykohrafichni systemy hramatychnoho typu ta yikh zastosuvannya
v za-sobakh avtomatyzovanoho opratsyuvannya movy. In: Avtoref. dys. kand. tekhn. nauk:
spets. 10.02.21, Kyiv, Ukraine (2011)
29. Martynenko, B.K.: Yazyki i translyatsii: Ucheb. Posobiye. In: Izd. 2-ye, ispr. i dop. – SPb.:
Izd-vo S.-Peterb. un-ta, (2008)
30. Marchenko, O.O.: Alhorytmy semantychnoho analizu pryrodnomovnykh tekstiv. In:
Avtoref. dys. na zdobuttya nauk. stupenya kand. fiz.-mat. nauk: spets. 01.05.01. Kyiv,
Ukraine (2005)
31. Noskov, S.A.: Samouchitel' nemetskogo yazyka. Deutsch für sie. Nauka, Kyiv, Ukraine
(1999)
32. Partyko, Z.V.: Prykladna i komp'yuterna linhvistyka. In: Afisha, Lviv, Ukraine (2008)
33. Vysotska, V.: Linguistic Analysis of Textual Commercial Content for Information Re-
sources Processing. In: Modern Problems of Radio Engineering, Telecommunications and
Computer Science, TCSET’2016, 709–713 (2016)
34. Pentus, A.Y., Pentus, M.R.: Teoriya formal'nykh yazykov: Uchebnoye posobiye. In: Izd-
vo TSPI pri mekhaniko-matematicheskom f-te MGU, Moscow (2004)
35. Popov, E.V.: Obshcheniye s EVM na yestestvennom yazyke. Nauka, Moscow (1982)
36. Postnikova, O.M.: Nimetsʹka mova. Rozmovni temy: leksyka, teksty, dialohy, vpravy. T.
1, A.S.K, Kyiv, Ukraine (2001)
37. Postnikova, O.M.: Nimetsʹka mova. Rozmovni temy: leksyka, teksty, dialohy, vpravy. T.
2, A.S.K, Kyiv, Ukraine (2001)
38. Potapova, H.M.: Morfonolohiya viddiyeslivnoho slovotvorennya (na materiali slo-
votvirnykh hnizd z vershynamy - diyeslovamy ta viddiyeslivnykh slovotvirnykh zon). In:
Dys. kand. nauk: 10.02.02, Ukraine (2008).
39. Rusachenko, N.P.: Morfonolohichni protsesy u slovozmini ta slovotvori
staroukrayins’koyi movy druhoyi polovyny XVI – XVIII st. In: Avtoreferat dysertatsiyi na
zdobuttya naukovoho stupenya kandydata filolohichnykh nauk, http://auteur.corneille-
moliere.com/?p=history&m=corneille_moliere&l=rus, last accessed 2019/11/21.
40. Torosyan, O.M.: Funktsionalʹni kharakterystyky pryslivnykiv miry ta stupenya v suchasniy
anhliysʹkiy movi. In: avtoref. dys. na zdobuttya nauk. stupenya kand. filol. na-uk,
http://disser.com.ua/contents/6712.html, last accessed 2019/11/21.
41. Turysheva, O.O.: Porushennya ramkovoyi konstruktsiyi v suchasniy nimetsʹkiy movi:
funktsionalʹnyy aspekt, normatyvnyy status. In: Avtoref. dys. kand. filol. nauk: spets.
10.02.04 (2012)
42. Ukrayins’kyy pravopys. In: In-t movoznavstva im. O.O. Potebni NAN Ukrayiny, In-t ukr.
movy NAN Ukrayiny, Nauk. dumka, Kyiv, Ukraine (2007)
43. Vysotska, V., Hasko, R., Kuchkovskiy, V.: Process analysis in electronic content com-
merce system. In: Proceedings of the International Conference on Computer Sciences and
Information Technologies, CSIT 2015, 120-123 (2015)
44. Fomichev, V.S.: Formal'nyye yazyki, grammatiki i avtomaty. In:
http://www.proklondike.com/books/thproch/, last accessed 2019/11/21.
45. Chomsky, N.: O nekotornykh formal'nykh svoystvakh grammatik. In: Kiberneticheskiy
sbornik, 5, 279-311. (1962)
46. Chomsky, N., Miller, G. A.: Formal'nyy analiz yestestvennykh yazykov. In: Kibernetich-
eskiy sbornik, 1, 231-290. (1965)
47. Chomsky, N.: Yazyk i myshleniye. In:Publikatsii OSiPL. Seriya monografiy, 2. (1972)
48. Chomsky, N.: Sintaksicheskiye struktury. In: Sbornik Novoye v lingvistike, 2, 412-527.
(1962)
49. Chepurna, Z.V.: Transformatsiya poryadku sliv u prostomu rechenni pry perekladi z
nimetsʹkoyi movy ukrayinsʹkoyu. In: Naukovi zapysky, 89(1), 232-236. (2010)
50. Sharov, S.A.: Sredstva komp'yuternogo predstavleniya lingvisticheskoy informatsii. In:
http://www.ksu.ru/eng/science/ittc/vol000/002/, last accessed 2019/11/21.
51. Korobchinsky, M., Vysotska, V., Chyrun, L., Chyrun, L.: Peculiarities of Content Forming
and Analysis in Internet Newspaper Covering Music News, In: Computer Science and In-
formation Technologies, Proc. of the Int. Conf. CSIT, 52-57 (2017)
52. Kanishcheva, O., Vysotska, V., Chyrun, L., Gozhyj, A.: Method of Integration and Con-
tent Management of the Information Resources Network. In: Advances in Intelligent Sys-
tems and Computing, 689, Springer, 204-216 (2018)
53. Naum, O., Chyrun, L., Kanishcheva, O., Vysotska, V.: Intellectual System Design for
Content Formation. In: Computer Science and Information Technologies, Proc. of the Int.
Conf. CSIT, 131-138 (2017)
54. Vysotska, V., Lytvyn, V., Burov, Y., Gozhyj, A., Makara, S.: The consolidated infor-
mation web-resource about pharmacy networks in city, CEUR Workshop Proceedings,
239-255 (2018)
55. Chyrun, L., Vysotska, V., Kis, I., Chyrun, L.: Content Analysis Method for Cut Formation
of Human Psychological State, Proceedings of the 2018 IEEE 2nd International Confer-
ence on Data Stream Mining and Processing, DSMP 2018, 139-144 (2018)
56. Chomsky, N.: Three models for the description of language. In: I. R. E. Trans. PGIT 2,
113-124. (1956)
57. Chomsky, N.: On certain formal properties of grammars, Information and Control 2. In: A
note on phrase structure grammars, Information and Control 2, 137-267, 393-395. (1959)
58. Chomsky, N.: On the notion «Rule of Grammar». In: Proc. Symp. Applied Math., 12.
Amer. Math. Soc. (1961)
59. Chomsky, N.: Context-free grammars and pushdown storage. In: Quarterly Progress Re-
ports, 65, Research Laboratory of Electronics, M. I. T. (1962)
60. Chomsky, N.: Formal properties of grammars. In: Handbook of Mathemati-Mathematical
Psychology, 2, ch. 12, Wiley, 323-418. (1963)
61. Chomsky, N.: The logical basis for linguistic theory. In: Int. Cong. Linguists, (1962)
62. Chomsky, N., Miller, G. A.: Finite state languages. In: Information and Control 1, 91-112.
(1958)
63. Chomsky, N., Miller, G. A.: Introduction to the formal analysis of natural languages. In:
Handbook of Mathematical Psychology 2, ch. 12, Wiley, 269-322. (1963)
64. Chomsky, N., Schützenberger M.P.: The algebraic theory of context-free languages. In:
Computer programming and formal systems, North-Holland, Amsterdam, 118–161 (1963)
65. English Verbs (Part 1) – Basic Terms. In: http://sites.google.com/si
te/englishgrammarguide/Home/english-verbs--part-1----basic-terms, last accessed
2019/11/21.
66. Vysotska, V., Chyrun, L., Chyrun, L.: Information Technology of Processing Information
Resources in Electronic Content Commerce Systems. In: Computer Science and Infor-
mation Technologies, CSIT’2016, 212-222 (2016)
67. Lytvyn, V., Vysotska, V., Uhryn, D., Hrendus, M., Naum, O.: Analysis of statistical meth-
ods for stable combinations determination of keywords identification. In: Eastern-
European Journal of Enterprise Technologies, 2/2(92), 23-37 (2018)
68. Lytvyn, V., Vysotska, V., Pukach, P., Brodyak, O., Ugryn, D.: Development of a method
for determining the keywords in the slavic language texts based on the technology of web
mining. In: EasternEuropean Journal of Enterprise Technologies, 2(2-86), 4-12 (2017)
69. Su, J., Sachenko, A., Lytvyn, V., Vysotska, V., Dosyn, D.: Model of Touristic Information
Resources Integration According to User Needs, 2018 IEEE 13th International Scientific
and Technical Conference on Computer Sciences and Information Technologies, CSIT
2018 – Proceedings 2, 113-116 (2018)
70. Lytvyn, V., Vysotska, V., Dosyn, D., Lozynska, O., Oborska, O.: Methods of Building In-
telligent Decision Support Systems Based on Adaptive Ontology. In: International Confer-
ence on Data Stream Mining and Processing, DSMP 2018, 145-150 (2018)
71. Burov, Y., Vysotska, V., Kravets, P. Ontological approach to plot analysis and modeling.
CEUR Workshop Proceedings, Vol-2362, 22-31 (2019)
72. Chyrun, L., Kis, I., Vysotska, V., Chyrun, L.: Content monitoring method for cut for-
mation of person psychological state in social scoring, 2018 IEEE 13th International Sci-
entific and Technical Conference on Computer Sciences and Information Technologies,
CSIT 2018, 106-112 (2018)
73. Lytvyn, V., Pukach, P., Bobyk, І., Vysotska, V.: The method of formation of the status of
personality understanding based on the content analysis. In: Eastern-European Journal of
Enterprise Technologies, 5/2(83), 4-12 (2016)
74. Lytvyn, V., Vysotska, V., Rzheuskyi, A.: Technology for the Psychological Portraits For-
mation of Social Networks Users for the IT Specialists Recruitment Based on Big Five,
NLP and Big Data Analysis. In: CEUR Workshop Proceedings, Vol-2392, 147-171.
(2019)