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<article xmlns:xlink="http://www.w3.org/1999/xlink">
  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Automated Identification of Metaphors in Annotated Corpus (Based on Substance Terms)</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Olena Levchenko</string-name>
          <email>levchenko.olena@gmail.com</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Oleh Tyshchenko</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Marianna Dilai</string-name>
          <email>mariannadilai@gmail.com</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Lviv Polytechnic National University</institution>
          ,
          <addr-line>Bandera Str., 12, Lviv, 79000</addr-line>
          ,
          <country country="UA">Ukraine</country>
        </aff>
      </contrib-group>
      <abstract>
        <p>The automatic or automated metaphor identification remains a challenging problem. The methods proposed so far have been mostly developed for the English language and can be roughly divided into two groups: intended for annotated and non-annotated corpora. In addition, neural networks are used. It should also be noted that the application of recently developed methods for measuring the degree of semantic association of collocation components (T-score, MI, logDice, etc.) fails to detect metaphorical expressions. Previously, we presented a method of automated identification of metaphorical expressions (adjective + noun) for non-annotated corpora of Ukrainian prose texts, based on the analysis of dictionary definitions. This paper describes a method of automated identification of metaphors in the semantically annotated corpus of texts. This algorithm is based on the theoretical propositions and readings of metaphor within the framework of Conceptual Metaphor Theory. The methodology contains an empirical stage at which structural-semantic models of metaphors are detected and classified based on the semantic category of the words in the right-hand position. The performance analysis and the evaluation of the method's effectiveness are presented.</p>
      </abstract>
      <kwd-group>
        <kwd>1 Metaphor</kwd>
        <kwd>annotated corpus</kwd>
        <kwd>substance nouns</kwd>
        <kwd>automated identification of metaphor</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>1. Introduction</title>
      <p>
        The automatic/automated metaphor identification still remains a challenging problem. The
methods introduced so far have been mostly developed for the English language and divided into the
methods designed for semantically annotated, metaphorically annotated and non-annotated corpora.
A detailed analysis of the approaches used today is presented in [
        <xref ref-type="bibr" rid="ref1 ref2 ref3 ref4">1, 2, 3, 4</xref>
        ] and others.
      </p>
      <p>
        It should be noted that different methods of automated metaphor identification are based on
different theoretical readings of metaphor; however, the most modern approaches are grounded on the
Conceptual Metaphor Theory [
        <xref ref-type="bibr" rid="ref5 ref6">5, 6</xref>
        ]. Given various interpretations of metaphor, researchers use
different terminology: ‘promising metaphorical words’ [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ]; aspect words, abstractness of the aspect
words [
        <xref ref-type="bibr" rid="ref7 ref8">7, 8</xref>
        ] and others.
      </p>
      <p>
        VUAMC corpus is an example of a metaphorically annotated corpus of the English language,
which is annotated applying the MIPVU methodology (Metaphor Identification Procedure Vrije
Universiteit) [
        <xref ref-type="bibr" rid="ref9">9</xref>
        ]. This technique includes revealing the basic meaning of the word and then
determining the degree of contrast between the basic and contextual meanings. To avoid subjectivism,
two or more annotators are involved in this procedure and are to reach an agreed decision [
        <xref ref-type="bibr" rid="ref9">9</xref>
        ].
      </p>
      <p>
        Previously, we developed a method of automated identification of metaphorical expressions
(adjective + noun) for non-annotated corpora of Ukrainian prose texts, based on the analysis
of dictionary definitions [
        <xref ref-type="bibr" rid="ref10">10</xref>
        ]. It has been successfully applied in a number of studies [
        <xref ref-type="bibr" rid="ref11 ref12">11, 12</xref>
        ], which
proved the effectiveness of the proposed method. In addition, the Master's thesis, carried out under
our supervision, describes structural-semantic models of zoomorphic metaphors in the semantically
non-annotated corpus of prose texts [
        <xref ref-type="bibr" rid="ref13">13</xref>
        ].
      </p>
      <p>
        This paper presents a method for automated identification of metaphors based on substance terms
in the semantically annotated corpus of texts. It should be noted that there are a number of principles
of semantic annotation of corpora [
        <xref ref-type="bibr" rid="ref14">14</xref>
        ]. The proposed method is based on theoretical provisions about
metaphor within the cognitive theory of metaphor. The analysis was conducted using GRAC corpus
[
        <xref ref-type="bibr" rid="ref15">15</xref>
        ]. Since GRAC V10 contains semantic annotation of only the most frequent words, we made
an attempt to semantically classify the collocates in order to test the hypothesis, using the principles
of semantic classification applied in the RNC [
        <xref ref-type="bibr" rid="ref16">16</xref>
        ].
      </p>
    </sec>
    <sec id="sec-2">
      <title>2. Theoretical linguistic background</title>
      <p>
        In the ‘precognitive’ period G. Sklyarevska identified the following types of regular metaphorical
transference (cognitivists instead of the term metaphorical transference mostly use the term blending
of conceptual domains): 1) OBJECT → OBJECT; 2) OBJECT → HUMAN BEING; 3) OBJECT →
PHYSICAL WORLD; 4) OBJECT → MENTAL WORLD; 5) OBJECT → ABSTRACTION;
6) ANIMAL → HUMAN BEING; 7) HUMAN BEING → HUMAN BEING; 8) PHYSICAL
WORLD → MENTAL WORLD [
        <xref ref-type="bibr" rid="ref17">17</xref>
        ] (see Fig. 1).
      </p>
      <p>OBJECT</p>
      <p>↑
OBJECT</p>
      <p>HUMAN
BEING</p>
      <p>↑
OBJECT</p>
      <p>PHYSICAL
WORLD</p>
      <p>↑
OBJECT</p>
      <p>MENTAL
WORLD</p>
      <p>↑
OBJECT</p>
      <p>↑
OBJECT</p>
      <p>HUMAN
BEING</p>
      <p>↑
ANIMAL</p>
      <p>HUMAN
BEING</p>
      <p>↑
HUMAN
BEING</p>
      <p>
        It has been revealed that conceptualization of mental states is characterized by personification,
perception of emotions as liquids, fire, light, elements (verbalization by the terms of these concepts)
[
        <xref ref-type="bibr" rid="ref18">18</xref>
        ]. O. Levchenko's phraseological study presents a range of metaphors within the verbalization
of mental states: STATE IS FORCE (FIRE, COLD (FROST), WIND, FLUID (WATER), LIVING
BEING (BEAST, RIVAL), LOCUS, CONTAINER; NORMAL STATE IS BALANCE, BODY IS
CONTAINER OF STATES [
        <xref ref-type="bibr" rid="ref19">19</xref>
        ].
      </p>
      <p>Thus, formalizing metaphorical models, we can speak of a ‘metaphorical hierarchy’ (which
is somewhat different from the semantic hierarchy of features): mental states (feelings, cognition,
speech) are metaphorized in terms of physiological states (life, death, body temperature, hunger),
personification (a living being – a human being, an animal), elements, flora or substance, but not vice
versa; physiological states are metaphorized by personification (a living being – a human being,
an animal), elements, flora or substance. The research hypothesis is that the combination, in our case,
of nouns belonging to different levels of hierarchy in terms of their semantics should indicate
the formation of a metaphor (the greater the interconceptual distance, the more likely it is a
metaphor). Substance nouns are at a lower level of the hierarchy than nouns belonging to semantic
categories/thematic classes r:abstr, t:be, t:be:exist, t:ment, t:humq, t:behav, t:psych, t:psych:emot,
t:speech, etc. In terms of substance semantics, a number of mental states are metaphorized (see
Table 1).</p>
      <p>
        We can state that the metaphor ANGER IS POISON is universal, it has various manifestations
in the Slavic languages: Ukr. псувати/зіпсувати кров ‘spoil/have spoiled one’s blood’ 1) ‘to be
nervous, irritated’; 2) ‘to cause someone a lot of trouble; to make someone nervous, to irritate
someone’ [
        <xref ref-type="bibr" rid="ref20">20</xref>
        ]; Bulg. тровя (отравям/отровя) кръвта на някого ‘poison one's blood’ [
        <xref ref-type="bibr" rid="ref21">21</xref>
        ]; Pol.
psuć komuś krew, napsuć krwi ‘wprawiać w zły humor; drażnić, dokuczać ‘to spoil one's blood, to put
someone in a bad mood; tease’ [22], although in the above examples we do not observe the use of the
actual term poison, in contrast to: Bulg. държи ме ядът ‘anger holds me’ [23], where poison is
‘strong irritation, malice, anger’; изкарвам/изкарам (изливам/излея) си яда ‘pour out your anger’;
яд ме е ‘I'm angry’ [23].
hunger,
temperature
      </p>
      <p>
        J. Dunn concludes that metaphor is a gradient phenomenon: certain metaphorical expressions are
characterized by a higher degree of metaphoricity, others are less metaphorical. The researcher
is convinced that the problem of different systems of metaphor identification lies in the fact that such
systems are based on binary division, and the phenomenon in question is of a gradient nature [24].
Therefore, he proposes to determine the degree of metaphoricity of the expression depending on its
metaphorical saturation [24]. The degree of metaphoricity is a very subjective feature, its
identification directly depends on the experience of the annotator. Interestingly, many works on
metaphor discuss a problem of classification of the phenomenon and assessment of its metaphoricity.
For example, Yu. Badryzlova notes: “in some cases, it is problematic to unambiguously classify
a meaning as a basic meaning or a non-basic meaning” [
        <xref ref-type="bibr" rid="ref3">3</xref>
        ]. However, we entirely agree that metaphor
is a complex and diverse phenomenon. The abovementioned properties are manifested in different
types of metaphors (structural – word, phrase, sentence, text (a metaphor that grows into an allegory
within the text); conceptual – associated with different ways of conceptualization; perception by
‘degree of metaphoricity’, etc.). We also agree that different procedures should be used to identify
different types of metaphors.
      </p>
      <p>‘Traditional’ linguistic analysis, in particular within cognitive linguistics, consists of three stages,
namely identification, interpretation and explanation [25]. J. Charteris-Black claims that “metaphor
identification is initially concerned with ideational meaning – that is, identifying whether they are
present in a text and establishing whether there is a tension between a literal source domain and
a metaphoric target domain. Metaphor interpretation is concerned with interpersonal meaning – that
is, identifying the type of social relations that are constructed through them. Metaphor explanation
is concerned with textual meaning: that is, the way that metaphors are interrelated and become
coherent with reference to the situation in which they occur” [26]. The data necessary for the
automated metaphor identification are obtained at the stage of interpretation (when the blended
conceptual domains get formalized description in the form of classification into semantic categories/
thematic classes).</p>
      <p>
        In this paper at the stage of ‘human’ identification of the metaphor we view collocations of the
formal-grammatical model SUBSTANCE NOUN (ОТРУТА, БАЛЬЗАМ, НЕКТАР, МЕД
‘POISON, BALM, NECTAR, HONEY’) + NOUN. The second component of collocation is classified
based on a particular semantic category/thematic class it belongs to. Previously, a comparative
technique was proposed by Turney [
        <xref ref-type="bibr" rid="ref6">6</xref>
        ], but the analysis of ‘the mixture of abstract and concrete
words’ was carried out within the sentence.
      </p>
      <p>
        In linguistics the metaphors of the model in question are called genitive metaphors (because the
second noun is mostly in the genitive case) or metaphors-comparisons. However, it is necessary to
take into account another property of such metaphors. In the course of metaphorization, we can
observe a complete and partial transfer of terms at the verbal level from blended conceptual domains.
For example, cf. баламутити голови кому ‘to muddy one's head’ 1) ‘to fool someone’, 2) ‘to incite
someone to bad actions, deeds’ [
        <xref ref-type="bibr" rid="ref20">20</xref>
        ]; ловитися/впійматися на гачок (на вудочку) ‘to be caught on a
hook’ (on a fishing rod) [
        <xref ref-type="bibr" rid="ref20">20</xref>
        ], закидати/закинути вудку (гачок, гака) ‘to throw a fishing rod
(hook)’ [
        <xref ref-type="bibr" rid="ref20">20</xref>
        ]. The phraseological unit includes the component голова ‘head’, which belongs to the
conceptual domain HUMAN BEING, and баламутити ‘to muddy’ belongs to the conceptual domain
WATER. In the examples ловитися/впійматися на гачок (на вудочку, закидати/закинути вудку
(гачок, гака) ‘catch on a hook (on a fishing rod), throw a fishing rod (hook)’, the components belong
to the conceptual source domain FISHERY [27]. Thus, the metaphors of the model SUBSTANCE
NOUN + NOUN contain terms of two conceptual domains, which provides explicit markers for
automatic identification of the minimal metaphorical context. In fact, the substance noun
metaphorizes the second component in the collocation.
      </p>
    </sec>
    <sec id="sec-3">
      <title>3. Results and discussion</title>
      <p>Thus, based on the corpus data, we have identified 643 contexts with the component отрута
‘poison’, in particular in 415 cases the word is used literally and in 228 contexts it is used
metaphorically. It should be noted that words/collocations in quotation marks can be considered
metaphorical if there are no markers of intertextuality. We have singled out the following cases of
literal use (see Table 2).
волхв ‘magician’ 1, гер ‘herr’ 1, Гофман
‘Hoffman’ 1, злочинець ‘criminal’ 1,
Калиновський ‘Kalynovsky’ 1, Клаус</p>
      <p>‘Klaus’ 1, князь ‘prince’ 2, колега
‘colleague’ 1, лікар ‘doctor’ 2, пацієнт
‘patient’ 2, Пилип'юк ‘Pylypyuk’ 1,
Серафима ‘Seraphim’ 1, спеціалісти
‘specialists’ 1, хазяїн ‘owner’ 1, людина
‘person’ 3, мисливець-убивця ‘killer</p>
      <p>hunter’ 5
квітка ‘flower’ 1, листя ‘leaves’ 1, посів
‘sowing’ 1, зілля ‘potion’ 1, рослина
‘plant’ 2, цикута ‘hemlock’ 1, анчар
‘antiar’ 1, гриб ‘mushroom’ 3, колючка
‘thorn’ 1, кураре ‘curare’ 28, плющ ‘ivy’ 2,</p>
      <p>поганка ‘toadstool’ 1
The word отрута ‘poison’ is followed by</p>
      <p>a punctuation mark
Гаспид ‘elapid’ 5, чортище ‘devil’ 1, аспид
‘elapid’ 2, василіск ‘basilisk’ 5, гідра</p>
      <p>‘hydra’ 2, потвора ‘monster’ 1
вогонь ‘fire’ 1, наркотик ‘narcotic’ 1,
актиній ‘sea anemone’ 2, газ ‘gas’ 1, дим
‘smoke’ 1, кисень ‘oxygen’ 1, ліки
‘medication’ 1, діоксин ‘dioxin’ 5,</p>
      <p>речовина ‘substance’
слід ‘should’ 3, треба ‘must’ 5
обличчя ‘face’ 5, лице ‘face’ 1
кров ‘blood’
cтріла ‘arrow’
ікло ‘fang’ 1, голова ‘head’ 2</p>
      <p>організм ‘organism’
організація ‘organization’, рятунок</p>
      <p>‘rescue’
мед ‘honey’ 1, абсент ‘absinthe’ 1
cпецслужба ‘special service’
орган ‘part of body’
страва ‘dish’
нирка ‘kidney’
залоза ‘gland’
плоть ‘flesh’
гостряк ‘sharp point’
джунглі ‘jungle’
м'ясо ‘meat’</p>
      <p>t:plant r:concr
t:animal t:stuff r:concr
t:stuff r:concr</p>
      <p>r:mod
pt:partb r:concr pc:hum</p>
      <p>t:stuff r:concr t:liq
t:tool r:concr top:rod
pt:partb pc:animal r:concr</p>
      <p>pc:hum
t:living r:concr
r:concr:org r:abstr
t:food t:stuff r:concr</p>
      <p>bbr r:concr t:org
hi:class pc:hum pc:animal</p>
      <p>t:tool:mus
op:horiz r:concr t:tool:dish
pc:hum pt:partb:organ</p>
      <p>r:concr
pc:hum pt:partb:organ</p>
      <p>r:concr
pc:hum t:stuff r:concr</p>
      <p>pt:constit
pc:tool:instr r:concr pt:part</p>
      <p>pc:tool:weapon
pt:aggr t:space r:concr</p>
      <p>sc:plant
pt:aggr t:stuff r:concr
25
16
14
8
6
6
4
3
3
2
2
1
1</p>
      <p>sc:partb
pt:aggr:aggrpl t:money
r:concr sc:money:banknote</p>
      <p>hi:class
pt:partb pc:animal r:concr
qc:space t:space r:concr
qc:stuff pt:qtm r:concr</p>
      <p>r:concr
r:concr pt:part
pc:tool:weapon
r:concr t:org
r:propn t:org
r:stuff r:concr t:liq
sc:constr:build t:space</p>
      <p>r:concr
t:access t:tool:cloth r:concr
top:cover
t:degr:max
t:group sc:hum pt:aggr</p>
      <p>r:concr
t:hum r:propn t:persn
t:space r:concr pt:part</p>
      <p>pc:space
t:space top:mineshaft</p>
      <p>t:constr r:concr
t:tool top:contain pc:stuff</p>
      <p>pt:element r:concr
t:tool:instr t:tool r:concr</p>
      <p>d:dim
top:contain r:concr</p>
      <p>t:tool:dish
top:horiz top:spher t:astr</p>
      <p>t:space r:concr
top:stripe t:space r:concr</p>
      <p>r:abstr
r:abstr t:card
t:physiol r:abstr</p>
      <p>r:abstr
r:abstr t:disease
r:abstr t:param t:size
sc:hum t:pers r:abstr
pt:aggr:aggrpl t:param</p>
      <p>r:concr
t:group pt:set r:concr
sc:hum r:abstr
t:physiol r:abstr
t:physiol t:be:disapp r:abstr
t:psych t:perc r:abstr
1
1
1
1
1</p>
      <p>The obtained results contain 11 errors. In a number of cases of the literal use of the word отрута
‘poison’ in the right-hand position there are words belonging to the semantic categories/thematic
classes which hypothetically should indicate the metaphorical nature of the word отрута ‘poison’:
Але спричинений отрутою біль негайно повертається, і птахи знову біжать до води ‘But the
pain caused by the poison immediately returns and the birds run to the water again’ (H. Quiroga,
Cuentos de la Selva, 1946); Поспішиш — і пожалкуєш. Пекуча отрута болем відізветься у тілі.
А кожна бджолина сім'я має свій «характер», потрібні індивідуальний підхід… ‘Hurry up and
you'll regret it. The burning poison will resonate in the body. And each bee family has its own
"character", requires an individual approach…’ (Journal Ukrainian Beekeeper, 1992); Тут ще
зосталась половина, її доволі буде нам, щоб на собаці отрути силу (sc:hum t:pers r:abstr pt:aggr:
aggrpl t:param r:concr; GRAC: 1:abst&amp;amp; able: 2:abst:physio&amp;amp; able: 3:abst: 4:abst:param:
5:conc:hum:collect: 6:abst:quantit:max) звідать ‘There is still half left, it will be enough for us to
find out the force of poison giving it to the dog’. Собака здохне – тебе живим у землю закопаєм
‘Should the dog die, we will bury you alive in the ground’ (I. Karpenko-Karyi, The evil spark will
burn the field and disappear itself, 1893).</p>
      <p>The accuracy of the results depends on the stylistic type of the text, prose or poetry. “The success
of the identification systems varies significantly across genres and sub-classes of metaphor” [24].
False identification is found in texts of scientific or popular science styles that have not been deleted
from the search query, such texts are more saturated with abstract terminology: При менших дозах
отрути смерть (t:physiol t:be:disapp r:abstr; GRAC: 1:abst:disappear: 2:abst:physio) настає через
кілька хвилин. При цьому спостерігаються задишка, судоми, втрата свідомості, відчуття…
‘Given lower doses of poison death comes in a few minutes. It is accompanied by shortness of breath,
convulsions, loss of consciousness, sensation’ (I.O. Kontsevich &amp; B.V. Mykhailychenko, Forensic
Medicine. Textbook, 1997); Особливо сильно впливає гашиш. При отруєнні цією отрутою
видіння виникають одне за одним ‘Hashish has a particularly strong effect. When poisoned by this
poison, visions appear one after another’ (M. Rubakin, Among Mysteries and Miracles, 1962); Під
час проведення сеансів з отримання отрути методом (r:abstr) електростимуляції ведуть
облік кількості отриманої отрути від кожної бджолиної сімї… ‘During the sessions for
obtaining poison by the method (r: abstr) of electrical stimulation, the amount of poison received from
each bee family is recorded’ (Journal Pasika, 34, 2005), etc.</p>
      <p>It should be noted that in the model SUBSTANCE NOUN (ОТРУТА, БАЛЬЗАМ, НЕКТАР,
МЕД ‘POISON, BALM, NECTAR, HONEY’) + NOUN the second noun is mostly in the genitive
case, functioning as a non-agreed attribute. Therefore, the verb in the sentence semantically agrees
with the conceptual sphere, in our case, of substance nouns. In other words, the prototype poison is a
liquid: В її душу вливалась крапля за краплею гірка отрута книжок, що видавалися масовими
тиражами в колишній панській Польщі ‘The bitter poison of books published in mass circulation
in the former lordly Poland poured into her soul drop by drop’ (Poison, Free Ukraine, 1940); Таким
чином, від жовтеняти до переспілого більшовика в свідомість суспільства вливали гадючу
отруту ненависті до героїв визвольних змагань на західноукраїнських землях ‘Thus, from Little
Octobrist to the overmature Bolshevik, a viper's poison of hatred for the heroes of the liberation
struggle in Western Ukraine was infused into the consciousness of society’ (V. Palyvoda, Memoirs of
a Ukrainian Insurgent and Long-Term Gulag Prisoner, 2001); Отрута осередку вливається
в дитячі душі і сіє розпусту ‘The poison of the center flows into children's souls and sows
debauchery’ (S. Yefremov, Diary, 1925). Sometimes the second component of collocations is in the
instrumental case, for example, отрута владою ‘poison by power’; in addition, in the word
combination отруту вогнем ‘poison by fire’ the instrumental case depends on the verb випалити
‘to burn’. Thus, the identification of metaphors through the semantics of the verb in this case will be
ineffective, in contrast to contexts in which the abstract concept is an agent.</p>
      <p>In total, 225 metaphors with a component отрута ‘poison’ were identified, 206 metaphors were
identified correctly, and 18 were identified incorrectly by semantic categories/thematic classes. We
have revealed the following units in the right-hand position in the literal sense (see Table 3).
Inaccurate results are obtained in poetic context, for instance: Квіт заполярної півсонної теплиці /
Квіт на який пролив бліду отруту місяць / Чиї брати цвітуть на смітниках понурі ‘The flower
of the polar half-asleep greenhouse / The flower on which moon shed a pale poison / Whose brothers
bloom in the dumps gloomily’ (V. Nezval, Five Minutes Past the Town, 1972 (translated by
A. Malyshko)); А неба пес крилатий гострим дзьобом, Омоченим в отруту вуст твоїх, / Мені
шматує серце, й виринає / Огидне кодло привидів, поріддя Безодні темрявої снів ‘And the sky's
winged dog with a sharp beak, Dipped in the poison of your lips, / Torns my heart to pieces, and
emerges / Disgusting brood of ghosts, the offspring of the Abyss of Dark Dreams’ (Yuri Klen in the
context of Ukrainian neoclassicism, 2004). In general, in a number of cases we are dealing with
extended metaphors, to the analysis of which a different approach should be applied (syntactic roles,
analysis of abstraction/sentence specificity): Можливо, але я тільки продовжую гру, яку почав ти;
я шукаю на твою отруту протиотруту, я вливаю в тебе стільки недовіри, що ти зможеш
виблювати її і здоровим повернутись додому ‘Perhaps, but I only continue the game you started,
I'm looking for an antidote to your poison, I'm instilling so much distrust in you that you can vomit it
out and come home healthy’ (P. Van Aken, Slapende honden, 1972, translation).
ненависть ‘hatred’ 14, шовінізм
‘chauvinism’ 7, ідеалізм ‘idealism’ 6,
брехня ‘lies’ 5, націоналізм ‘nationalism’
4, зрада ‘betrayal’ 3, влада ‘power’ 2,
гріх ‘sin’ 2, єресь ‘heresy’ 2, перемога
‘victory’ 2, нетерпимість ‘intolerance’ 2,
утіха ‘consolation’ 1, заціпеніння</p>
      <p>‘numbness’ 1, абстракціонізм
‘abstractionism’ 1, авторитаризм
‘authoritarianism’ 1, більшовизм
‘bolshevism’ 2, біологія ‘biology’ 1, буття
‘genesis’ 1, влада ‘power’ 1, гнів ‘anger’
1, демократія ‘democracy’ 1, євангелізм
‘Evangelism’ 1, ідея ‘idea’ 1, історія
‘history’ 1, лібералізм ‘liberalism’ 1,</p>
      <p>лузерство ‘being a loser’ 1,
людиноненависництво ‘misanthropy’ 1,</p>
      <p>малодушність ‘cowardice’ 1,
махновщина ‘makhnovism’ 1, мистецтво</p>
      <p>‘art’ 1, модернізм ‘modernism’ 1,
москвофільство ‘Russophilia’ 1, нацизм</p>
      <p>‘Nazism’ 1, недовір'я ‘distrust’ 1,
ностальгія ‘nostalgia’ 1, оргія ‘orgy’ 1,
патріотизм ‘patriotism’ 1, поп-культура
‘pop culture’ 1, популізм ‘populism’ 1,
постправда ‘post-truth’ 1, поцілунок</p>
      <p>‘kiss’ 1, презирство ‘contempt’ 1,
пропаґанда ‘propaganda’ 1, расизм
‘racism’ 1, реваншизм ‘revanchism’ 1,</p>
      <p>революція ‘revolution’ 1, сіонізм
‘Zionism’ 1, скептицизм ‘scepticism’ 1,</p>
      <p>агресивність ‘aggression’ 1,
бездуховність ‘spirituality’ 1, безнадія</p>
      <p>‘hopelessness’ 1, буденність
‘mundaneness’ 1, в'їдливість ‘causticity’
1, недбальство ‘negligence’ 1,
t:psych:emot r:abstr</p>
      <p>t:humq r:abstr
t:psych:emot r:abstr t:hum</p>
      <p>t:speech r:abstr
t:physiol t:psych r:abstr</p>
      <p>r:abstr t:poss
t:ment t:psych r:abstr
t:ment t:neg r:abstr</p>
      <p>t:ment r:abstr
t:humq t:psych:emot r:abstr</p>
      <p>t:psych r:abstr
t:physiol t:be:disapp r:abstr</p>
      <p>t:ment r:abstr
t:manif:emot r:abstr
t:impact r:abstr
t:changest r:abstr
t:be:exist r:abstr
t:word r:concr r:abstr
t:perc r:abstr
t:sound r:abstr
t:physiol r:abstr</p>
      <p>t:loc r:abstr
t:be:disapp r:abstr
13
12
8
5
5
4
4
4
4
3
3
3
3
3
3</p>
      <p>
        The lexemes серце, кров, сльози ‘heart, blood, tears’ in fiction texts can acquire symbolic
meaning. “Organs such as heart, blood, tears etc. are symbols verbalizing relevant mental and
intellectual states (verbalization is based on the idea that these organs can be both producers and
patients)” [
        <xref ref-type="bibr" rid="ref19">19</xref>
        ]. Thus, for literary texts it is important to take into account the symbolic meaning
(which can be the result of both metaphorization and metonymization), in particular, a number of
somatisms: Весь в свого батька! — виказує жінка те, що завжди в неї на вустах. То її власна
отрута серця, яку, до речі, мати виробляє для себе і за власним рецептом ‘Like father like
son! — The woman utters what is always on her lips. It is her own poison of the heart, which, by the
way, mother produces for herself and according to her own recipe’ (N. Odala, Who are you and what
are you doing here, 2011). In GRAC, the word серце ‘heart’ is semantically tagged as
1:conc:body:part: 2:abst:psych:emot: 3:abst: 4:conc:hum:posit, which indicates that the word has a
number of meanings and ‘abstract’ ones are second and third in frequency. It is important to note that
this tag does not imply a negative evaluation. However, in the phraseological systems of the
Ukrainian language, the concept of ГНІВ ‘ANGER’ is also verbalized through the idea of changes in
the heart functioning (the word серце ‘heart’ is synonymous with гнів, злість, пересердя, іритація,
пасія ‘anger, rage, anger, irritation, passion’), increased blood pressure and blood pollution: Ukr.
серце набіга ‘heart raids’; серця додати ‘to add heart’ (cf. Ukr. докладати/докласти душі (серця)
‘apply soul (heart) to sth’ – Belarus. сэрца мець на каго ‘to have heart on someone’ — Bulg.
сърцето му се налива с кръв ‘his heart is filled with blood’ [
        <xref ref-type="bibr" rid="ref19">19</xref>
        ]. Contexts such as ‘Гостя кивала
головою і втирала солону отруту сліз, а коли йшла, то їй уже було легше’ ‘The guest shook her
head and rubbed salty poison of tears, and when she walked, it was already easier for her’
(O. Pechorna, Sinner, 2011) prove that the word сльоза ‘tear’ should be annotated with the semantic
tag t:manif:emot in the corpus.
      </p>
      <p>
        We have revealed some interesting examples regarding the semantic categories: metaphor: …Ми
перемогли місто! Святкуй зі мною нашу перемогу! Тепер ми можемо будувати своє життя,
вільне від отрути міста (sc:constr:build t:space r:concr; GRAC 1:conc:loc:container)!.., при
цьому виникає специфічний вибір оповідної програми на підставі пізнавальних просторів…
‘We defeated the city! Celebrate our victory with me! Now we can build our lives free from the
poison of the city!.., and there is a specific choice of narrative program based on cognitive spaces…’
(T. A. Marchak, Ideological and artistic specificity of G. Mykhailychenko's sketch The City, 2010);
Отрута Петербурґа, міста туманів і примар, міста підступної “імітації Європи” – вже
зробила своє; Вона, як пошесть, понесла туди отруту руїн. Ти мало напився її ? — Але що ж
тут робити, тату? Ми ж помремо! ‘The poison of St. Petersburg, the city of mists and ghosts, the
city of insidious "imitation of Europe" — has already done its thing; Like a plague it carried the
poison of ruins there. Have you drunk enough of it? – But what shall we do, Dad? We will die!’ (M.
Ivchenko, The last minutes, 1919); non-metaphor: Ще тисячі людей були змушені залишити свої
оселі й переїхати з уражених отрутою сіл (sc:constr:build t:space r:concr; GRAC
1:conc:loc:container: 2:conc:loc: surface: 2:conc:hum:collect) у безпечні регіони. ‘Thousands more
people were forced to leave their homes and move from poisoned villages to safe regions’ (on-line
newspaper; Ukraina Moloda, 2011). The dictionary definitions of the words місто, село ‘city,
village’ do not explain the binary opposition city – village, given in fiction and philosophical texts,
where the units denoting loci are used in the civilizational sense. Moreover, the word село ‘village’ is
used as a metonymy, which is reflected in the dictionary definition and, accordingly, in the semantic
tagging of GRAC. Marking the ambiguity of words in tagging represents the semantics accurately
(дерево ‘tree’ |1:conc:plant: higherclass: 2:conc:stuff| життя ‘life’ |1: abst:exist: 2:abst:time:
3:abst|), but requires algorithms of contextual distinction between ambiguity and homonymy (as in the
case of the word руїна ‘ruin’, the ambiguity of which is given in the dictionaries) and, accordingly,
clarification of the metaphor identification methodology, which should take into account the
configurations of semantic tags. One of the compilers of the GRAC corpus states: “In cases of
ambiguity, ie, when a lemma may have more than one set of semantic tags due to being used in
multiple senses, all such sets are listed in the semantic lexicon, leaving the problem of semantic
disambiguation for later stages” [Starko 2020]. The solution to this problem can be additional
verification of individual results using the method proposed in [
        <xref ref-type="bibr" rid="ref10">10</xref>
        ].
      </p>
      <p>The formal approach does not work when the word отрута ‘poison’ collocates with words that
belong to the thematic class pt:set | pt:aggr – group and collective objects (меблі, людство ‘furniture,
humanity’): Усе ж разом узяте виконує одну й ту ж роль духовної отрути народу (pt:set
sc:hum r:concr; GRAC 1:conc:hum:group:higherclass) ‘All together performs the same role of
spiritual poison of the people’ (V. Koptilov, Letters from Paris; letter G6; devilry and mysticism,
1974); До того, що все краще в нашій історії сфальшовано, заплямовано зміїною отрутою
недругів. ‘To the fact that all the best in our history is falsified, tainted with snake poison of enemies’
(A. Palamar, Degradation, 2004); …веде своє, ще не порушене революційною отрутою військо
(t: group pt:aggr:aggrpl r:concr sc:hum; GRAC 1:conc:hum:group:collect) ‘…leads its army, which
has not yet been violated by the revolutionary poison’ (S. Mazlakh, V. Shakhray, The union of
proletariat and bourgeoisie against world imperialism, 1919). In some cases, the clarifying factor for
identification may be the left-hand environment: духовної отрути, революційною отрутою
‘spiritual poison, revolutionary poison’.</p>
      <p>We have also revealed not very common cases when the word combination отрута ‘poison’ +
collocate (t:animal r:concr) is metaphorical: …гроші, лицемірство, багатство, блиск і зовнішній
шик брали верх над усім. Ця отрута п'явкою впивалася в її свідомість, точила її серце
‘…money, hypocrisy, wealth, brilliance and external chic prevailed over everything. This poison like
a leech penetrated her consciousness, sharpened her heart’ (Poison, Free Ukraine, 1940). This is
a typical example of an extended metaphor. This metaphor is lexicographically fixed: впиватися
(впитися) п'явкою (як п'явка) в серце; мов (немов, наче і т. ін.) п'явки за серце ссуть ‘to get like
a leech into the heart; like (as if, etc.) leeches suck the heart’ [28].</p>
      <p>Another example shows the generally typical phenomenon of a combination of metaphor and
metonymy – metaphthonymy: Наприклад, духовну смерть широких мас, що вдень тяжко
працюють, а ввечорі засуджені на отруту кінотеатру і телевізії, вони вважають цілком
нормальною. ‘For example, the spiritual death of the masses, who work hard during the day and in
the evening are doomed to the poison of cinema and television, they consider quite normal’ (C.
Miłosz, The captive mind, 1983, translated by B. Struminskyi).</p>
      <p>We observe comparable lists of semantic tags of noun-collocates for metaphors and
nonmetaphors analyzing implementations of the model БАЛЬЗАМ, НЕКТАР, МЕД ‘BALM, NECTAR,
HONEY’ + noun. Obviously, the frequency of specific semantic tags of noun-collocates are different
for each of the analyzed words, as well as the ratio of metaphors and non-metaphors (see Table 4).
The most frequent of the analyzed words are the least metaphorical.</p>
      <p>We have revealed a high percentage of metaphors among the collocations with the component
бальзам ‘balm’: Не страх за шпигунство Галкіна, ні сподівання «приказа» вже не триволоіли
його; жінчина любов, тихі, розумні розмови з тестем наче бальзам спокою вливались в його
серце... ‘Neither the fear of Galkin's espionage nor the hope of the "order" bothered him; a woman's
love, quiet, intelligent conversations with his father-in-law like a balm of peace poured into his
heart…’ (O. Konyskyi, Yuriy Gorovenko. Chronicle of Troubled Times, 1883); І, думав Піфагор над
смислом земного буття, болісно перебирав у свідомості мудрі вислови філософів та шукачів
Істини і не міг покласти на рану серця цілющого бальзаму заспокоєння… ‘And, Pythagoras
thought about the meaning of earthly existence, he painfully went over in his mind the wise sayings of
philosophers and seekers of Truth and could not put on the wound of the heart the healing balm of
soothing…’ (O. Berdnyk, Veil of Isis, 1969); Взагалі мрія це бальзам душі ‘In general, a dream is a
balm of the soul’ (F. Odrach, On uncertain ground); І тепер його душа колисалася на хвилі світлої
печалі, купалась у бальзамі співчуття, який так щедро виливала на нього Мері ‘And now his
soul was floating in a sad serenity. It was embalmed in the sympathy that Mary so generously poured’
(Aldous Huxley, Crome Yellow, translated by V. Vyshnevyi, 1978). It should be noted that in all the
above sentences we can see extended metaphors and/or a combination of metaphor and metonymy,
but in this paper, we consider only the minimal metaphorical context.</p>
      <p>Interestingly, metaphorically synonymous terms бальзам ‘balm’ and нектар ‘nectar’ verbalize
the concepts which only partially intersect: Може, тобі здавалося принизливим почуття дівчини,
котру ти ще недавно напував нектаром знання, зібраним з квіток всіх віків і народів?
‘Perhaps you found humiliating the feelings of the girl you recently drank the nectar of knowledge
collected from flowers of all ages and peoples?’ (O. Berdnyk, The darkness does not ignite the hearth,
1993); – Ви п'яні, правда? – перебила мавка. — Я п'яний нектаром кохання ‘– You're drunk,
aren't you? – The maw interrupted. – I am drunk with the nectar of love’ (O. Turyansky, Son of the
Earth, 1933); …вона, справді, мов та бджола, невтомно трудилася – несла своєму народові
цілющий нектар освіченості і культури – попри всі безкінечні імперські утиски. ‘She, indeed,
like a bee, worked tirelessly – carried to her people the healing nectar of education and culture –
despite all the endless imperial oppression’ (I. Kuchernyuk, Magazine Native Land in socio-political
and cultural life of Ukraine (1905-1916.), 2016); Геній Карла XII пірвав їх, як гураган, вихопив з
рідних хат, з обіймів батьків, жінок і дітей і нестримним летом ніс назустріч невідомих
подій у невідомих краях, і як безпритомних, як напоєних узваром забуття і задурманених
нектаром слави, кидав в обійми терпіння, каліцтва і смерті ‘The genius of Charles XII tore
them apart like a hurricane, snatched them from their homes, from the arms of parents, wives and
children, and carried them to unknown events in unknown lands, and as unconscious, as intoxicated
with forgetfulness and intoxicated by the nectar of glory throw them in the arms of ordeal, injuries
and deaths’ (B. Lepkyi, Poltava, 1929)</p>
      <p>Collocations with the component мед ‘honey’ are metaphorized the least frequently. Typical are
collocations with the components кохання, знання, вчення ‘love, knowledge, teaching’: В духмяні
ложа манила лукава гречка. Медом кохання гусли очі, як соти… ‘Sly buckwheat beckoned in the
fragrant bed. The honey of love filled the eyes like honeycombs’ (I. Kalynets, Dance of Thirst, 1964);
...вдивлявся в шафи і скриньки, які ховали в собі різні папки, картотеки, картки — щільники,
повні гіркого меду знання, зібраного з тисяч людських уст, або як я ще називав їх у хвилини
гіркоти й досади, катакомби людського життя – пояснював, свідчив, ставив підписи…
‘Looked at the closets and boxes with various folders, files, cards – seals, full of bitter honey of
knowledge gathered from thousands of human lips, or as I called them in moments of bitterness and
annoyance, the catacombs of human life – explained, testified, signed’ (H. Auderska, The fruit of the
pomegranate tree, translated by D. Andrukhiv, 1978); Ця війна, – каже Ань, – зібрала гіркий мед
досвіду тисячолітньої боротьби ‘This war, says An, gathered the bitter honey of the experience of
the millennial struggle’ (B. Dymytrova, translated by M. Syngaivskyi, Underground Sky. Vietnamese
Diary – 72, 1973); Той, хто не куштує меду життя з глека смутку, не розуміє, що таке
життя… ‘He who does not taste the honey of life from the pitcher of sorrow does not understand
what life is like…’ (S. Tkachuk, Kaleidoscope, 1985).</p>
      <p>In our opinion, to optimize the process, any automated identification of metaphors should begin
with building a database of stabilized metaphors, because in many cases, considering the minimum
metaphorical context will not give the expected results. Such stabilized metaphors are phraseologiсal
units that vividly illustrate collocations with the component мед ‘honey’ (although in modern texts,
given the stability, they are used in a transformed form): Не варто псувати бочку меду ложкою
дьогтю, – сказав Дінні ‘You should not spoil a barrel of honey with a spoon of tar, – said Danny…’
(K. S. Pritchard, The Roaring Nineties, translated by L. Solonko, 1985); Багатьом здається, що при
владі дають мед ложкою їсти ‘It seems to many that the authorities get a spoonful of honey to eat’
(Internet newspaper; Vysokyi Zamok, 2006).</p>
      <p>Thus, the study revealed conceptual domains that are blended during metaphorization. We
calculate the semantic distance between words that verbalize the concepts in question (using [29]).
“In distributional semantics, words are usually represented as vectors in the multidimensional space of
their contexts. Semantic similarity is calculated as the cosine proximity between vectors of two words
and can have values within [-1 ... 1] (in practice, only values above 0 are often used). A value of 0
means that these words do not have similar contexts and their meanings are not related to each other.
The value 1 indicates full identity of contexts and, consequently, the proximity of meaning” [29].</p>
      <p>Indices of semantic similarity of the substance nouns are within the range of 0.43-0.62. The
indices of semantic similarity of the words included in the minimal metaphorical contexts are much
lower (0.002-0.33), the range of indices of non-metaphorical collocations is 0.097-0.53 (see table 6).
On the one hand, vector analysis shows valuable information about interconceptual distance,
indicating a tendency to metaphorization for words that are at a ‘greater distance’, and on the other
hand, it can be used only as a supplementary parameter to identify metaphors.
4. Conclusions</p>
      <p>Thus, distributional semantic analysis of collocations of the formal model NOUN (t:stuff
r:concr) + NOUN gives 90–94.89% of accurate results. The findings show that the collocations of the
model NOUN (t:stuff r:concr) + NOUN (r:abstr; t:psych, t:speech, t:word, t:text, t:physiol, t:ment,
t:manif:emot, t:be:exist, etc.) are metaphorical.</p>
      <p>Identification procedures require additional clarification for the collocations of the model NOUN
(t:stuff r:concr) + NOUN (t:space, t:hum, t:group, t:topon, etc.) in fiction texts. The interpretation of
collocations that include somatic symbols is problematic by the classification of nouns into semantic
categories/thematic classes used in this study.</p>
      <p>Furthermore, it has been revealed that the model NOUN (t:stuff r:concr) + NOUN (t:disease,
t:size, t:param, t:physiol, t:psych, t:perc) is non-metaphorical in scientific and popular science texts.</p>
      <p>Semantically annotated corpora provide a basis for creating techniques for automatic/automated
metaphor identification. Obviously, specific algorithms for metaphor identification depend
on the principles of semantic tagging used in a particular corpus of texts. However, the starting point
of identification is the idea of a ‘metaphorical hierarchy’: the concepts that are at higher levels are
metaphorized in terms of the concepts of lower levels; the greater the interconceptual distance, the
more likely the creation of metaphorical meaning is. The distribution of conceptual verbalizers at
different levels (by a certain semantic category/thematic class) allows us to describe formal models of
potential metaphors.</p>
    </sec>
    <sec id="sec-4">
      <title>5. References</title>
      <p>[22] SJP – Słownik języka polskiego, Wydawnictwo Naukowe PWN SA, 2003.
[23] Bulgarian Explanatory Dictionary, Eurodictxp. URL: http:// koralsoft.dir.bg/dict.php
[24] J. Dunn, How linguistic structure influences and helps to predict metaphoric meaning, Cognitive</p>
      <p>Linguistics 24(1) (2013) 33-66.
[25] N. Fairclough, Critical Discourse Analysis: the Critical Study of Language, Longman, London/</p>
      <p>New York, 1995.
[26] J. Charteris-Black, Corpus Approaches to Critical Metaphor Analysis, Palgrave Macmillan UK,
2004.
[27] O. Levchenko, Phraseological symbolism: linguo-cultural aspect, Lviv, 2005.
[28] Dictionary of the Ukrainian Language, vol. 8, pp. 416. URL: http://sum.in.ua/p/8/416/1
[29] Comprehensive information system of scientific research "Automated workplace of a
researcher". URL: http://icybcluster.org.ua:34145/</p>
    </sec>
  </body>
  <back>
    <ref-list>
      <ref id="ref1">
        <mixed-citation>
          [1]
          <string-name>
            <given-names>T.</given-names>
            <surname>Strzalkowski</surname>
          </string-name>
          ,
          <string-name>
            <given-names>G. A.</given-names>
            <surname>Broadwell1</surname>
          </string-name>
          ,
          <string-name>
            <given-names>S.</given-names>
            <surname>Taylor</surname>
          </string-name>
          , L. Feldman1,
          <string-name>
            <given-names>B.</given-names>
            <surname>Yamrom1</surname>
          </string-name>
          ,
          <string-name>
            <given-names>S.</given-names>
            <surname>Shaikh</surname>
          </string-name>
          , T. Liu,
          <string-name>
            <given-names>K.</given-names>
            <surname>Cho</surname>
          </string-name>
          ,
          <string-name>
            <given-names>U.</given-names>
            <surname>Boz</surname>
          </string-name>
          , I. Cases, K. Elliott,
          <article-title>Robust Extraction of Metaphors from Novel Data</article-title>
          ,
          <source>in: Proceedings of the First Workshop on Metaphor in NLP</source>
          ,
          <article-title>The American Association for Computational Linguistics (NAACL-</article-title>
          <year>2013</year>
          ), Atlanta, USA,
          <year>2013</year>
          , pp.
          <fpage>67</fpage>
          -
          <lpage>76</lpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref2">
        <mixed-citation>
          [2]
          <string-name>
            <given-names>T.</given-names>
            <surname>Veale</surname>
          </string-name>
          ,
          <string-name>
            <given-names>E.</given-names>
            <surname>Shutova</surname>
          </string-name>
          ,
          <string-name>
            <given-names>B.</given-names>
            <surname>Klebanov</surname>
          </string-name>
          ,
          <article-title>Metaphor: a computational perspective</article-title>
          ,
          <source>Synthesis Lectures on Human Language Technologies</source>
          , Morgan Claypool, San Rafael, California,
          <year>2016</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref3">
        <mixed-citation>
          [3]
          <string-name>
            <surname>Yu</surname>
          </string-name>
          . Badryzlova,
          <article-title>Experience of corpus modeling of factors of metaphoricity based on Russian verbs, Computational linguistics and intellectual technologies: on the materials of the international conference "</article-title>
          <source>Dialogue</source>
          <year>2017</year>
          " Moscow, May 31 - June 3,
          <year>2017</year>
          . URL: http://www.dialog-
          <volume>21</volume>
          .ru/media/3898/badryzlovayug.pdf
        </mixed-citation>
      </ref>
      <ref id="ref4">
        <mixed-citation>
          [4]
          <string-name>
            <given-names>O.</given-names>
            <surname>Levchenko</surname>
          </string-name>
          ,
          <string-name>
            <given-names>N.</given-names>
            <surname>Romanyshyn</surname>
          </string-name>
          , Modern approaches to automated identification of metaphor, Bulletin of Lviv University, Philological series
          <volume>70</volume>
          (
          <year>2019</year>
          )
          <fpage>288</fpage>
          -
          <lpage>298</lpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref5">
        <mixed-citation>
          [5]
          <string-name>
            <given-names>E.</given-names>
            <surname>Shutova</surname>
          </string-name>
          ,
          <string-name>
            <given-names>L.</given-names>
            <surname>Sun</surname>
          </string-name>
          ,
          <string-name>
            <given-names>A.</given-names>
            <surname>Korhonen</surname>
          </string-name>
          ,
          <article-title>Metaphor identification using verb and noun clustering</article-title>
          ,
          <source>Proceedings of the 23rd International Conference on Computational Linguistics</source>
          , Beijing,
          <year>2010</year>
          , pp.
          <fpage>1002</fpage>
          -
          <lpage>1010</lpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref6">
        <mixed-citation>
          [6]
          <string-name>
            <given-names>P. D.</given-names>
            <surname>Turney</surname>
          </string-name>
          ,
          <string-name>
            <given-names>Y.</given-names>
            <surname>Neuman</surname>
          </string-name>
          ,
          <string-name>
            <given-names>D.</given-names>
            <surname>Assaf</surname>
          </string-name>
          ,
          <string-name>
            <given-names>Y.</given-names>
            <surname>Cohen</surname>
          </string-name>
          ,
          <article-title>Literal and metaphorical sense identification through concrete and abstract context</article-title>
          ,
          <source>in: The 2011 Conference on Empirical Methods in Natural Language Processing</source>
          , Edinburgh,
          <year>2011</year>
          , pp.
          <fpage>680</fpage>
          -
          <lpage>690</lpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref7">
        <mixed-citation>
          [7]
          <string-name>
            <given-names>M.</given-names>
            <surname>Coltheart</surname>
          </string-name>
          ,
          <article-title>The mrc psycholinguistic database</article-title>
          ,
          <source>The Quarterly Journal of Experimental Psychology Section A</source>
          <volume>33</volume>
          (
          <issue>4</issue>
          ) (
          <year>1981</year>
          )
          <fpage>497</fpage>
          -
          <lpage>505</lpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref8">
        <mixed-citation>
          [8]
          <string-name>
            <given-names>M.</given-names>
            <surname>Wilson</surname>
          </string-name>
          ,
          <article-title>Mrc psycholinguistic database: Machine-usable dictionary</article-title>
          , version
          <volume>2</volume>
          .00,
          <string-name>
            <surname>Behavior</surname>
          </string-name>
          re-search methods, instruments, &amp; computers,
          <volume>20</volume>
          (
          <issue>1</issue>
          ) (
          <year>1988</year>
          )
          <fpage>6</fpage>
          -
          <lpage>10</lpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref9">
        <mixed-citation>
          [9]
          <string-name>
            <given-names>G. J.</given-names>
            <surname>Steen</surname>
          </string-name>
          ,
          <string-name>
            <given-names>A. G.</given-names>
            <surname>Dorst</surname>
          </string-name>
          ,
          <string-name>
            <given-names>J. B.</given-names>
            <surname>Herrmann</surname>
          </string-name>
          ,
          <string-name>
            <given-names>A.</given-names>
            <surname>Kaal</surname>
          </string-name>
          , T. Krennmayr, VU Amsterdam Metaphor Corpus,
          <year>2010</year>
          . URL: http://ota.ahds.ac.uk/headers/2541
        </mixed-citation>
      </ref>
      <ref id="ref10">
        <mixed-citation>
          [10]
          <string-name>
            <given-names>O.</given-names>
            <surname>Levchenko</surname>
          </string-name>
          ,
          <string-name>
            <given-names>N.</given-names>
            <surname>Romanyshyn</surname>
          </string-name>
          ,
          <string-name>
            <given-names>D.</given-names>
            <surname>Dosyn</surname>
          </string-name>
          ,
          <article-title>Method of automated identification of metaphoric meaning in adjective + noun word combinations (based on the Ukrainian language)</article-title>
          ,
          <source>in: CEUR Workshop Proceedings</source>
          , Vol.
          <volume>2386</volume>
          ,
          <source>Workshop proceedings of the 8th International conference on Mathematics. Information technologies. Education, MoMLeT&amp;DS</source>
          <year>2019</year>
          , pp.
          <fpage>370</fpage>
          -
          <lpage>380</lpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref11">
        <mixed-citation>
          [11]
          <string-name>
            <given-names>O.Y.</given-names>
            <surname>Petruk</surname>
          </string-name>
          ,
          <string-name>
            <given-names>O.P.</given-names>
            <surname>Levchenko</surname>
          </string-name>
          ,
          <article-title>Identification of the metaphor model білий 'white' + noun by the method of quantitative analysis of dictionary definition, Young scientist</article-title>
          ,
          <volume>10</volume>
          (
          <issue>74</issue>
          ) (
          <year>2019</year>
          )
          <fpage>505</fpage>
          -
          <lpage>511</lpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref12">
        <mixed-citation>
          [12]
          <string-name>
            <surname>Ya</surname>
          </string-name>
          . Smuzhanytsia,
          <article-title>Automated identification of the metaphor model гіркий</article-title>
          /солодкий/прісний 'bitter/sweet/fresh' +
          <source>noun : Master's thesis</source>
          ,
          <year>2020</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref13">
        <mixed-citation>
          [13]
          <string-name>
            <surname>Yu</surname>
          </string-name>
          . Kyrylyuk,
          <article-title>Algorithm of automatic identification of zoomorphic metaphor</article-title>
          ,
          <source>Master's thesis</source>
          , Lviv,
          <year>2020</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref14">
        <mixed-citation>
          [14]
          <string-name>
            <given-names>V.</given-names>
            <surname>Starko</surname>
          </string-name>
          , Semantic Annotation for Ukrainian: Categorization Scheme, Principles, and Tools,
          <string-name>
            <surname>COLINS</surname>
          </string-name>
          ,
          <year>2020</year>
          , pp.
          <fpage>239</fpage>
          -
          <lpage>248</lpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref15">
        <mixed-citation>
          [15]
          <string-name>
            <given-names>M.</given-names>
            <surname>Shvedova</surname>
          </string-name>
          , R. von Waldenfels,
          <string-name>
            <given-names>S.</given-names>
            <surname>Yarygin</surname>
          </string-name>
          ,
          <string-name>
            <given-names>A.</given-names>
            <surname>Rysin</surname>
          </string-name>
          ,
          <string-name>
            <given-names>V.</given-names>
            <surname>Starko</surname>
          </string-name>
          ,
          <string-name>
            <given-names>M.</given-names>
            <surname>Wozniak</surname>
          </string-name>
          ,
          <string-name>
            <given-names>M.</given-names>
            <surname>Kruk</surname>
          </string-name>
          ,
          <article-title>General regionally annotated corpus of the Ukrainian language (GRAC), Kyiv</article-title>
          , Lviv, Yena,
          <fpage>2017</fpage>
          -
          <lpage>2021</lpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref16">
        <mixed-citation>
          <source>[16] National Corpus of the Russian Language</source>
          ,
          <fpage>2003</fpage>
          -
          <lpage>2006</lpage>
          . URL: https://ruscorpora.ru
        </mixed-citation>
      </ref>
      <ref id="ref17">
        <mixed-citation>
          [17]
          <string-name>
            <given-names>G.</given-names>
            <surname>Sklyarevskaya</surname>
          </string-name>
          ,
          <article-title>Metaphor in the language system</article-title>
          ,
          <source>Ros. AN</source>
          , Institute of Linguistic research, Science, St. Petersburg,
          <year>1993</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref18">
        <mixed-citation>
          [18]
          <string-name>
            <given-names>N.D.</given-names>
            <surname>Arutyunova</surname>
          </string-name>
          ,
          <article-title>Language and the human world, Languages of Russian culture</article-title>
          , Moscow,
          <year>1999</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref19">
        <mixed-citation>
          [19]
          <string-name>
            <given-names>O.P.</given-names>
            <surname>Levchenko</surname>
          </string-name>
          ,
          <article-title>Symbols in phraseological systems of the Ukrainian and Russian languages: a linguo-cultural aspect, Manuscript, The dissertation on competition of a scientific degree of the doctor of philological sciences</article-title>
          <source>in specialty 10.02.01 the Ukrainian language</source>
          ,
          <volume>10</volume>
          .
          <fpage>02</fpage>
          .02 the
          <string-name>
            <surname>Russian</surname>
            <given-names>language</given-names>
          </string-name>
          , Institute of Linguistics,
          <string-name>
            <surname>O.O. Potebnya NAS</surname>
          </string-name>
          of Ukraine, Kyiv,
          <year>2007</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref20">
        <mixed-citation>
          [20]
          <string-name>
            <given-names>V. M.</given-names>
            <surname>Bilonozhenko</surname>
          </string-name>
          ,
          <string-name>
            <given-names>L. S.</given-names>
            <surname>Palamarchuk</surname>
          </string-name>
          et al. (Eds.),
          <article-title>Phraseological dictionary of the Ukrainian language, Naukova dumka</article-title>
          , Кyiv,
          <year>1993</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref21">
        <mixed-citation>
          [21]
          <string-name>
            <given-names>A.</given-names>
            <surname>Koshelev</surname>
          </string-name>
          , M. Leonidova (Eds.),
          <article-title>Bulgarian-Russian phraseological dictionary</article-title>
          ,
          <source>Science and Art</source>
          , Moscow, Sofia,
          <year>1974</year>
          .
        </mixed-citation>
      </ref>
    </ref-list>
  </back>
</article>