=Paper= {{Paper |id=Vol-2969/paper42-CAOS |storemode=property |title=An Ontology for Ploke: Rhetorical Figures of Lexical Repetitions |pdfUrl=https://ceur-ws.org/Vol-2969/paper42-CAOS.pdf |volume=Vol-2969 |authors=Yetian Wang,Randy Allen Harris,Daniel M. Berry |dblpUrl=https://dblp.org/rec/conf/jowo/WangHB21 }} ==An Ontology for Ploke: Rhetorical Figures of Lexical Repetitions== https://ceur-ws.org/Vol-2969/paper42-CAOS.pdf

An Ontology for Ploke: Rhetorical Figures of Lexical
Repetitions
Yetian Wang, Randy Allen Harris and Daniel M. Berry
University of Waterloo, 200 University Ave. W., Waterloo, Ontario, Canada

Abstract
Ploke is a rhetorical device of lexical repetition, with multiple variations contingent on place of occur-
rence. It is widespread in all natural and artificial languages because it manages stability of reference
and predication. Syllogisms, for instance, are heavily dependent on positional repetition. Ploke also
influences the reader’s/hearer’s attention because of its appeal to neurocognitive affinities. A formal
knowledge representation of ploke is therefore valuable for any AI/NLP system. This paper proposes
an ontological model for ploke. We discuss components of different types of plokes and rhetorical fig-
ures in general, in terms of their form, their function, and the associated neurocognitive affinities that
affect attention.

Keywords
rhetorical figure, ontology, knowledge representation, computational rhetoric

1. Introduction
Rhetoric is the “ancient study of persuasion, with particular attention to the effects of expressive
style on belief, action, and knowledge” [1]. The use of rhetoric affects the style and effectiveness
of an utterance; “the meaning of an utterance is communicated through the relations among
its constituents, as well as their relations with contextual and cotextual elements” [2]. The
incorporation of rhetorical principles in current Artificial Intelligence (AI) and Natural Language
Processing (NLP) systems, collectively termed as “AI/NLP systems”, is therefore an important
area of study [1][2][3][4][5][6][7][8][9][10][11].
Devices of rhetoric called rhetorical figures which generate a set of attentional effects such as
salience, aesthetic pleasure, and mnemonic effect received by the audience, thus managing the
receiver’s attention. Common rhetorical figures, such as rhyme, metaphor, and sarcasm, that
are encountered in everyday conversations may be noticed easily. Other common rhetorical
figures that involve traits, such as repetition, semantic increase, and inverted concepts, may not
be as easily noticed. A rhetorical figure creates a “figure-and-ground landscape that focalizes
some details and put others in relief” [12]. e.g., communicators are attracted by the sound of the
words or phrases with repeated syllables in rhymes and by the connections established between
concepts in different domains when metaphors are used. Rhetorical figures are widespread in
all registers, genres, and dialects of all languages. There simply does not exist a pure literal

CAOS 2021: 5th Workshop on Cognition And OntologieS, held at JOWO 2021: Episode VII The Bolzano Summer of
Knowledge, September 11-18, 2021, Bolzano, Italy
" yetian.wang@uwaterloo.ca (Y. Wang); raha@uwaterloo.ca (R. A. Harris); dberry@uwaterloo.ca (D. M. Berry)
© 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
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language [2]. The study of rhetorical figures is multidisciplinary. The stylistic effects of figurative
language “are partially explained by semiosis (the relevance of signantia and signata for the basic
scheme/trope distinction), by linguistics (the elements focalized by the figure–syllables, and
words, for instance), and by cognitive neuroscience (the appeal to pattern biases like repetition
and similitude); in turn, they explain the stylistic effects of language” [12].
However, few of even the most ubiquitous rhetorical figures have received attention from
computer scientists (or even rhetoricians). One such example is ploke1 , rhetorical figures of
lexical repetition. That is, whenever a word, word string, or entire phrases or clauses is repeated,
it is a ploke, e.g., “very, very big”; “easy come, easy go”; “waste not, want not”. Rhetorical figures
code much valuable information at syntactic, semantic, and pragmatic levels. This information
can be incorporated to facilitate a wide range of AI/NLP applications such as conversational
agents, machine translation, authorship attribution, genre detection, sentiment analysis, etc.
This paper proposes an ontology for ploke and other rhetorical figures of lexical repetition in
terms of class, subclass, and their relations. We also represent concepts related to ploke and
rhetorical figures in general, e.g., form, function, neurocognitive affinity, etc., Section 2 describes
the current state of research and applications of rhetorical figures in AI/NLP. Then, Section
3 presents classes and relations that capture the high level concepts of rhetorical figures in
general. Section 4 discusses detailed concepts related to ploke in ontological terms. Section 5
concludes the paper with a discussion potential future research directions.

2. Related Work
Although rhetorical figures have been studied for millennia, the establishment of the subfield
Computational Rhetoric was fairly recent, where the importance of a computational model
for rhetorical figures was highlighted for various NLP applications such as argument mining,
authorship attribution, automated rhetorical figure detection, etc [3][4]. The idea of construction
an ontology for rhetorical figures was delivered more than a decade ago by Harris and Di
Marco [1][2] and has inspired a line of research of ontological models of rhetorical figures
[9][10][11][13][14][15][16] including research presented in this paper.
Ontologies are formal knowledge representation models that enable sharing of reusable and
inferable knowledge structures and data. The most cited definition of an ontology is from
Gruber: “An ontology is a formal, explicit specification of a shared conceptualization” [17]. In
simple words, an ontology is a set of axioms that define some commonly agreed concepts (i.e.
classes and their instantiation) and relations among them (i.e. object and datatype properties).
Harris et al. stated that rhetorical figures are “prime candidates for a cognitive ontology. They
are both richly, demonstrably cognitive, and richly, demonstrably valuable for NLP tasks like
argument mining” [2].
In previous work of O’Reily et al. [13] and Black et al. [14], an ontology was developed for the
rhetorical figure climax, a compound figure of gradatio and incrementum. A gradatio features a
sequence of words or phrases repetition at clause boundaries, i.e., anadiplosis. The sequence of
repeated words or phrases form an incrementum such that there is a semantic increase along the
repeated words or phrases [13]. Anadiplosis and gradatio are both rhetorical figures of lexical
1
Also spelled as ploce or ploche.
repetition. The authors defined anadiplosis in terms of elements, colons, and tokens. Gradatio is
a sequence of anadiploses. This paper extends their model to other rhetorical figures of lexical
repetition and incorporates notions of neurocognitive affinities such as repetition and position.
The goal of this paper is not about the details of a detection algorithm for rhetorical figures, but
rather to develop a unified ontological representation that facilitates various NLP applications,
one of which is the automatic detection and annotation for rhetorical figures. Existing detection
tools uses methods such as regular expressions [18], shallow parsing [5], machine learning
classifiers [19][20], ontologies [15][16], and hybrid approaches [6][7], almost all of which cover
implementation details related to ploke detection such as recognizing repetitions of a word or
phrase, positions, sentence boundaries, intentionality etc. within a given passage or corpus.
Although this paper treats all lexical repetitions as plokes, some detection tools treat repetition
of function words, stop-words, etc. as accidental or false-positives which are filtered according
to specific algorithms of the detection tools [2][12]. This line of work also sheds light on various
applications such text summarization [8], argument mining [11][21], authorship attribution
[6][7], and machine translation [22].

3. Rhetorical Figures and Attention
This section describes a general level ontological model for rhetorical figures. The ontology
includes a classification of rhetorical figures as well as related concepts such as linguistic
elements, neurocognitive affinities and attentional effects. This model is not intended to be
comprehensive but rather as a collection of upper level classes and relations that encapsulate
concepts of ploke presented in the next section. We use a capitalized word in a sans serif font to
indicate a class name, e.g., Ploke; a capitalized word in a typewriter font to indicate a relation,
e.g., Contain; a serif font with quotation marks for an example quotation of a rhetorical figure
or a part thereof, e.g., “All for one”; and text in a serif italic font for a variable denoting an
arbitrary instance of a class, e.g., passage1.
To the center of the ontology is the class Rhetorical Figure. A Rhetorical Figure, contained in
a Passage, causes the Passage to have Attention Effects on the Passage’s Receiver, as is shown
by the bolded path in Figure 1. A conventional classification of rhetorical figures is to classify
figures as schemes and tropes. A Scheme is a subclass of Rhetorical Figure that is characterized
by form such as phonology, morphology, lexis, and syntax. A scheme can be formed by, for
instance, an effective repetition or alternation of position of a word or phrase in a passage.
A Trope is a class in which the figures are heavily characterized by the semantics within the
passage. The following example demonstrates an instance of Scheme:

“All for one, one for all”[23] (Example 1)
Example 1 contains multiple rhetorical figures, including several plokes. A Ploke is a subclass
of Scheme whose form is a repetition of words. In this example, the repeated words are “all”,
“for”, and “one”. While Example 1 is most famous as an exemplum of antimetabole, reverse
lexical repetition (“all” and “one” repeat in reverse order), rhetorical figures often work together
to maximize cognitive appeal and constrain the range of rhetorical functions [24], and Example
is-a Passage Receiver

Entity Set/ Class

binary
relation

0,*
Linguistic Element Rhetorical Figure

Form Function

Token Clause ...

Trope Form Trope
Scheme Form Scheme

Antithesis Metaphor ...

Ploke Form Ploke ...

Neurocognitive
Attention Effect
Affinity

Antimetabole
... ... Anadiplosis Antimetabole Mesodiplosis
Form

Semantic
Balance Opposition Position Repetition ...
Opposition

Figure 1: Rhetorical Figure Ontology general overview

1 is no exception. It consists a number of different types of scheme in addition to antimetabole,
including mesodiplosis, anadiplosis, and others, which will be discussed in the next section.
A Rhetorical Figure consists of a Form and a Function2 . The Form of a Rhetorical Figure
consists of a set, possibly ordered, of Linguistic Elements. A linguistic element is one of a word,
syllable, phrase, clause, phoneme, lexeme, morpheme, sememe. Since this paper focuses on
ploke, we will omit details of other linguistic elements and focus our discussion on Token only,
which is defined in this paper as one word or a sequence of words, minimally interrupted. Token
is a subclass of Linguistic Elements. The Form of a Rhetorical Figure Triggers one or more
neurocognitive affinities. A Neurocognitive Affinity is a pattern recognized by a receiver’s brain
[2], e.g., Symmetry, Balance, Opposition, Position, Repetition, Semantic Opposition, autc3 .
These neurocognitive affinities, individually or conjointly, will generate Attention Effects such
as salience, aesthetic pleasure, or increase memorability [2].
The connection made by the neurocognitive affinities creates a coupling between a rhetorical
figure’s form and its function. The function becomes predicable when the form of a rhetorical
figure is recognized [2]. For example, lexical repetition of Token (i.e., the form) in Example 1
functions to stabilize reference for the concept conveyed to ensure that “all” and “one” refer
2
Also referred to as rhetorical function
3
Just as “etc.” = “and others”, so do “autc.” = “or (exclusive) others” and “velc.” = “or (nonexclusive) others”.
to the same entities [25]. The reversed repetition (i.e., the form) of antimetabole in Example 1
generates a focus on the reciprocal relationship (i.e., the function) [25]. The form of Example 1
triggers a balance (of structure), an opposition (“all” and “one”), and repetitions (“all”, “for”, and
“one”) each of which is a neurocognitive affinity. All figures present in Example 1 harmoniously
generate attentional effects such as salience, aesthetic pleasure, and memorability, thus a famous
quote was created [26]. There are other rhetorical figures such as parison and isocolon that
contribute to the attentional effects of Example 1. This paper focuses on ploke, rhetorical figures
of lexical repetition.

4. An Ontology for Ploke
4.1. Ploke: Figures of Lexical Repetitions
The terminological and conceptual history of rhetorical figures is uneven at best, and ploke
is a case in point. It is traditionally defined as “the intermittent or unpatterned reappearance
of a word” [27], distinguished from figures like antimetabole or anadiplosis, in which words
do exhibit patterns in their occurrences. But as Harris [12] argues, Ploke is better viewed as
a class of lexical repetition figures (otherwise unconnected in the classical tradition). To this
end, we follow Harris et al. [2] in making the distinction between Simple Ploke and Complex
Ploke. Simple Ploke is the unpatterned default repetition of words and Complex Ploke is the
class of figures, like Antimetabole and Anadiplosis, in which multiple occurrences of words are
positionally patterned, either with respect to each other (antimetabole) or to larger units of
discourse (anadiplosis). Simple Ploke has only one member (Conduplicatio, one of the many
synonyms used to designate unpatterned lexical repetition). Complex Ploke has many members
as shown in Figure 2. Definitions and examples of subtypes of Complex Ploke are shown below,
with the repeated tokens bolded. The definitions and examples are based on Harris and Di
Marco (2017) [28].

Anadiplosis: lexical repetition of a Token on both side of a clause or phrase boundary.

“. . . you won’t prevent poverty. Poverty being more than income . . . ” [21]

Antimetabole: lexical repetition of two Tokens in reverse orders.

“Ask not what your country can do for you. Ask what you can do for your
country.” [29]

Epanalepsis: lexical repetition directly across phrasal or clausal boundaries.

“Boys will be boys.”

Epanaphora: lexical repetition of a Token at the beginning of clauses or phrases, a synonym to
anaphora.

“That’s one small step for man, one giant leap for mankind.” [30]

Epiphora: lexical repetition of a Token at the end of clauses or phrases, a synonym to epistrophe.
“If I lend you money, I’m taking a risk. And I should carry that risk.” [21]

Epizeuxis: immediate lexical repetition of a Token.

“Long, long ago.”

Gradatio: A sequence of anadiploses.

“Man behaving strangely is confronted by police. Police shoot man. Man dies.”
[31]

Mesodiplosis: lexical repetition when of a Token in the middle of clauses or phrases.

“We were elected to change Washington, and we let Washington change us.” [32]

The use of these rhetorical figures generates a set of attentional effects linked to a number
of neurocognitive affinities of human mind such as balance and symmetry, and to its core,
repetition and position.

4.2. Form and Function of Ploke
Recall that a Rhetorical Figure consists of a Form and a Function. Ploke as a subclass of Scheme
which in turn is a subclass of Rhetorical Figure, inherits this property. The form of a ploke, i.e.,
PlokeForm, a subclass of Form, Triggers a set of subclasses of Neurocognitive Affinity such
as Repetition, Position, Balance, Opposition, autc. Each subclass of Ploke has a specific form
which triggers a set of neurocognitive affinities. For example, the form of an antimetabole such
as Example 1 is:

...𝐴...𝐵 ...𝐵 ...𝐴...

where 𝐴 and 𝐵 are Tokens being repeated (𝐴 = “all” and 𝐵 = “one”). The form of antimetabole
demonstrates a balanced structure with the reversed repetition of 𝐴 and 𝐵, therefore triggering
neurocognitive affinities of a reversed repetition which in turn contributes to affinities such
as balance and opposition. We will discuss the relations between forms and neurocognitive
affinities with details in the next section.
The most important functions of ploke are to stabilize reference and emphasize the concept
conveyed by the repetition. Repetition of a Token in a passage or speech stabilizes the reference
to increase its clarity in context. Fahnestock’s analysis suggests that repetitions are crucial
in scientific writings where it is important to reduce or eliminate ambiguity [25]. Another
function of ploke is to emphasize the concept conveyed by the repeated Token. The more a
word, phrase or clause is repeated, the more it stands out from a sentence or a passage. Both
stabilizing reference and emphasizing concept conveyed are functions related to ploke. In
addition, subclasses of ploke have specific functions such as to increase the significance of
quantity, reciprocality, and irrelevance of order, etc. which will be discussed in the following
paragraphs.
An antimetabole has several functions. A function of antimetabole is to convey the idea of
irrelevance of order, that is, the order or rank of 𝐴 and 𝐵 does not matter. For example, “Ladies
Linguistic
Element

hasForm Ploke
Token

hasLE Ploke Form Simple Complex
Ploke Ploke
triggers

Position Repetition Conduplicatio Anadiplosis Mesodiplosis Antimetabole ...

Figure 2: Ontological view of Ploke

and gentlemen, gentlemen and ladies”. Another function of an antimetabole is to generate a
focus on reciprocal relationship [25]. The reversed repetition often suggests a reciprocal relation
between the repeated words 𝐴 and 𝐵. For example, in propositional logic, the equivalence
relation 𝐴 ↔ 𝐵 is expressed as: 𝐴 → 𝐵 ∧ 𝐵 → 𝐴, which indeed is an antimetabole, i.e., it has
the form of . . . 𝐴 . . . 𝐵 . . . 𝐵 . . . 𝐴 . . .. More generally, let 𝑅1 and 𝑅2 be binary relations, 𝐴 and
𝐵 be atomic concepts, then a reciprocal relation between 𝐴 and 𝐵 can be represented as

𝑅1 (𝐴, 𝐵) * 𝑅2 (𝐵, 𝐴)

where the * can be any binary connective, e.g., ∧, ∨, →, or ↔, which does not affect the
antimetabole. This is represented graphically in Figure 3.

𝑅1
→
𝐴← 𝐵
𝑅2
Figure 3: Reciprocal relation between 𝐴 and 𝐵

In Example 1, the reversed repetition suggests an equivalent reciprocal obligation between
“all” and “one”, i.e., an entity of group, organization, or community supports an individual while
an individual contributes to that entity. Thus, let For be a binary relation, we have

For(“all”, “one”) → For(“one”, “all”)

Note that the symmetrical case in which 𝑅1 = 𝑅2 is achieved in combination with mesodiplo-
sis, i.e., the medial repetition of the word “for”. The function of irrelevance of order or rank also
applies in Example 1, thus the rank of “one” and “all” does not matter. Therefore Example 1
may also be expressed as:

“One for all, all for one”
Combining the expression above with the original Example 1 results in an equivalence relation

For(“all”, “one”) ↔ For(“one”, “all”)

Consider the following example in which 𝑅 exists between 𝐴 and 𝐵 but not equivalent.

“Anyone who thinks he has a solution does not comprehend the problem and
anyone who comprehends the problem does not have a solution.” [33]
(Example 2)
where 𝐴 = “has a solution” and 𝐵 = “comprehends the problem”. Converting it to propositional
logic we have,

(𝐴 → ¬𝐵) ∧ (𝐵 → ¬𝐴)

We cannot conclude the opposite, i.e., ¬𝐵 → 𝐴, anyone who does not comprehend the
problem has a solution. The formula above also resembles the form of an antimetabole. If we
abuse the notation and define an arbitrary relation IF-Then-Not such that

IF-Then-Not(𝐴, 𝐵) ≡ 𝐴 → ¬𝐵

Thus, the reciprocal relation conveyed is the IF-Then-Not relation between 𝐴 and 𝐵.

IF-Then-Not(𝐴, 𝐵) ∧ IF-Then-Not(𝐵, 𝐴)

Note that IF-Then-Not(𝐴, 𝐵) ≡ IF-Then-Not(𝐵, 𝐴) since (𝐴 → ¬𝐵) ≡ (𝐵 → ¬𝐴),
and can be reduced to ¬(𝐴 ∧ 𝐵). Example 2 basically repeated ¬(𝐴 ∧ 𝐵) in different forms,
one starts from 𝐴 and ends at 𝐵, one starts from 𝐵 and ends at 𝐴. The function of completeness
is evoked by the antimetabole in the sense that: doesn’t matter where you start, whether you
think you have a solution or you comprehend the problem, a solution does not exist.

IF-Then-Not(𝐴, 𝐵) ≡ ¬(𝐴 ∧ 𝐵) ≡ IF-Then-Not(𝐵, 𝐴)

An antimetabole usually conveys a relation 𝑅1 and 𝑅2 between 𝐴 and 𝐵. Usually a mesodiplo-
sis suggests that 𝑅1 = 𝑅2 . Recall the formula with an abstract binary connective,

𝑅1 (𝐴, 𝐵) * 𝑅2 (𝐵, 𝐴)

The binary relation * can be simple logical connectives such as ∨, ∧, →, 𝑜𝑟 ↔. In some cases *
is explicit as in Newton’s third law of motion, i.e., “If you press a stone with your finger, the finger
is also pressed by the stone” [34]; and in other cases it is implicit as in Example 1 and Example
2. The functions of plokes, or any rhetorical scheme, are best achieved when accompanied by
forms that evoke or trigger neurocognitive affinities that harmonize with the functions.
4.3. Cognitive Affinity: Repetition and Position
Repetition is an important and fundamental aspect of language and cognition. It is possibly
the most fundamental neurocognitive affinity that builds the foundation of brain activities and
thus human minds [12]. Repetition emphasizes and stabilizes a sequence in memory and thus
is essential for memorization. Most people tend to repeat a formula or a phone number in
order to remember it [28]. Ploke is the repetition of Tokens. In terms of attentional effects of
ploke, it is the repetitions that generate the salience effect on the repeated Tokens. That is,
the more a Token repeats, the more noticeable it becomes, and thus the concept conveyed by
that Token becomes more memorable. As stated previously, the form of an antimetabole, i.e.,
. . . 𝐴 . . . 𝐵 . . . 𝐵 . . . 𝐴 . . . triggers a reversed repetition of 𝐴 and 𝐵 that resembles a balanced
structure as shown in Figure 4a.

→∘← → ∘∘ →
(a) (b)
Figure 4: (a) The form of antimetabole generates a point balance structure; (b) The form of anadiplosis
generates a step-wise energy flow. Modified based on [12][35]

Another example is the form of anadiplosis, i.e., . . . 𝐴.𝐴 . . . , which generates a focus point
that serves as a transition point of a step-wise energy flow as shown in Figure 4b. The repetition
at the final position of the boundary acts as the goal of the first clause, then the repetition at
the initial position of the successive clause acts as the source of that clause [12].
The position affinity is triggered by repetitions of a Token at different positions within a
phrase or clause. Positions can be immediately followed as in an epizeuxis, reversed as in an
antimetaoble, or proximal with respect to another token in a passage. A position can also be
the initial, medial, or final position with respect to a clause with in a passage.
Traditionally, neurocognitive affinities are viewed as independent entities. However, following
the ontological representation of concepts related to Ploke presented in this paper, it is reasonable
to view repetition and position as two primary neurocognitive affinities triggered by the form
of a ploke. That is, Repetition and Position are subclasses of Neurocognitive Affinity. All other
neurocognitive affinities triggered by forms of subclasses of Ploke are subclasses of Repetition
linked with specific orientation of positions that are subclasses of Position.
Repetition is the reoccurrence of an Element. The Element in this context may be referred to
as a Token, phrase, clause, or a repetition, e.g., figures such as antimetabole and gradatio have
nested repetitions. A Repetition consists of at least two Elements that refer to the same instance
of a Token. In this case, an Element can be viewed as an occurrence of a Token. An Element
has a Position which can be Before or After another Position. Thus the Elements’ Positions
impose some order, i.e., Before(position(e1), position(e2)) for Elements e1 and e2. Note that
position(e1) and position(e2) are functions which are in turn instances of the Position class. A
Repetition can be defined as follows:

∀rep, e1, e2.Repetition(rep) ∧ Element(e1) ∧ Element(e2)
∧ ElementOf(e1, rep) ∧ ElementOf(e2, rep)
→ RefersTo(e1, w) ∧ RefersTo(e2, w) ∧ Token(w)
∧ Before(position(e1), position(e2))

A Repetition can be an Unpatterned Repetition, Relative Repetition, Respective Repetition,
or a Nested Repetition. An unpatterned repetition is triggered by the form of a Conduplicatio, a
sublcass of Simple Ploke, in which repetitions are not constrained by position. Other subclasses
of Complex Ploke such as Epanaphora, Mesodiplosis, and Anadiplosis further restrict positions
of their elements with respect to the clauses that contain them4 . The form of each of these
figures triggers Constituent-Initial, Constituent-Medial, and Constituent-Final Repetition re-
spectively, all of which are subclasses of Relative Repetition. The form of Epizeuxis tirggers
Immediate Repetition, whille the form of an Antimetabole triggers Reversed Repeition. Both
are subclasses of Respective Repetition. Organization of sublcasses of Repetition is shown in
Figure 5.

Neurocognitive
Position
Affinity

Token Element Repetition

Unpatterned Relative Respective Nested
Repetition Repetition Repetition Repetition

Outer- Cross- Constituent-
Clause- Constituent- Constituent-
Immediate Between Reversed Gradatio
Boundary Boundary Beginning
Initial Medial Final
Repetition Repetition Repetition Repetition
Repetition Repetition Repetition Repetition Repetition

Figure 5: Ontological view of Repetition, a neurocognitive affinity

In Example 1, repetition of the word “all” can be represented by referring both e1 and e2 to
the word “all” as in Figure 6. Similarly, the repetition of the word “one” can be represented using
different sets of instances of Element referring to the word “one”. Both repetitions of “all” and
“one” are triggered by forms of subclasses of Ploke, more specifically, an Epanalepsis5 and an
Anadiplosis. Another repetition in Example 1 is formed by the word “for”, a Mesodiplosis. Each
of these three plokes triggers a subclass of Relative Repetition, i.e., Outer-Boundary Repetition,
Cross-Boundary Repetition and Constituent-Medial Repetition. Figure 7 demonstrates the
Cross-Boundary Repetition as an example.
The form of an Anadiplosis triggers the neurocognitive affinity of Cross-Boundary Repetition,
a subclass of Relative Repetition. Let there be an arbitrary instance c-b-rep1 of Cross-Boundary
Repetition that has Elements rep1e1 and rep1e2, each having its own instance of Position, i.e.,
4
A position can be an absolute position (e.g., position 0, 1, etc.) or a respective or relative position with respect
to another element, e.g., immediately after a word, beginning of a clause, etc. For simplicity, position refers to the
latter unless otherwise stated.
5
Let’s treat 𝐴 . . . , . . . 𝐴 as epanalepsis for now, although it refers to the repetition at the beginning and the
end of the same clause.
Token

Refers Refers
e1 To "all" To e2

Repetition

Element Element
rep
Of Of

postion Before postion
(e2) (e2)

Position

Figure 6: Example of Repetition using Example 1

position(rep1e1) and position(rep1e2). The elements of c-b-rep1 not only specify the order of
their positions with respect to each other, but also with respect to the clauses. A Clause is a
Linguistic Element that Contains Token. A Clause is connected to a Relative Position which
is a subclass of Position that represents a position within a clause. Other subclasses of Position
are Unpatterned Position and Respective Position. A Relative Position can be either Initial,
Medial, or Final. A Clause Precedes or Follows another Clause. A Clause can also be
Proximal to another Clause. Graphically, the classes Clause and Position can be represented
as in Figure 8. The positions of elements of c-b-rep1 must be instances of Final and Initial of
the clauses in which the anadiplosis is contained in. For example, let c1 and c2 be instances
of Clause and Precedes(c1, c2). The positions of elements rep1e1 and rep1e2 are located in
c1 and c2 respectively. In terms of Example 1, the string values of c1 and c2 are “All for one”
and “one for all” respectively. Both rep1e1 and rep1e2 refer to the word “one”. In this case,
the position of rep1e1 must be an end position of c1. Thus position(rep1e1) is an instance of
End that is linked to c1. Similarly, position(rep1e2) is an instance of Initial that is linked to c2.
Another relation between the clauses is the Proximal(c1, c2) to indicate proximity between the
clauses. Similarly, a Constituent-Initial, Constituent-Medial, and Constituent-Final Repetition
triggered by Epanaphora, Mesodiplosis, and Epiphora respectively, has both elements with
positions that are instances of Initial, Medial, and Final respectively. In the case of Epanalipsis,
positions of elements are the opposite of that in the case of Anadiplosis, i.e., rep1e1 and rep1e2
are instances of Initial and Final respectively.
Another subclass of Repetition is Nested Repetition, in which its elements are themselves
instances of Repetition. In other words, a Nested Repetition is the repetition of Repetitions.
This paper demonstrates Reversed Repetition, a subclasses of Nested Repetition while also a
subclass of Respective Repetition, triggered by the form of an Antimetabole.
The form of an antimetabole triggers a Reversed Repetition, which is a subclass of Repe-
tition. The elements of Reversed Repetition are Repetitions. Let rep1 and rep2 be instances
Ploke
Repetition Ploke
Form

Relative Repetition

Cross-
Anadiplosis
Boundary Anadiplosis
Form
Repetition

Clause c-b-rep1 Clause

"all for one" "one for all"

c1 Contain ElementOf Contain c2

rep1e1 RefersTo rep1e2

"one"

position(rep1e1) Before position(rep1e2)

Final Position Initial

Precedes
Proximal

Figure 7: Example of Cross Boundary Repetition using Example 1

of Repetition and rep1e1, rep1e2, rep2e1 and rep2e2 be elements of rep1 and rep2 defined as in
Figure 6 accordingly, then an instance revRep1 of Reversed Repetition can be defined as follows
and graphically in Figure 9:

ReversedRepetition(revRep1) ∧ ElementOf(rep1, revRep1)
∧ ElementOf(rep2, revRep1)
→ Before(position(rep1e1), position(rep2e1))
∧ Before(position(rep2e1), position(rep2e2))
∧ Before(position(rep2e2), position(rep1e2))

In Example 1, rep1e1, rep1e2 both refer to the word “all” and rep2e1, rep2e2 both refer to the word
“one”. The order of positions of the elements is, in conventional notation, 𝑟𝑒𝑝1𝑒1 < 𝑟𝑒𝑝2𝑒1 <
𝑟𝑒𝑝2𝑒2 < 𝑟𝑒𝑝1𝑒2. Note that in this case the positions are not instances of Relative Position, but
of Respective Position with relations Before and After representing the order of the position
of each element with respect to each other. Since relations Before and After are transitive,
the relation Before(position(rep1e1), position(rep1e2)) defined as part of the definition (i.e., the
dashed line in Figure 9) of rep1 is implicit from the definition of revRep1.
What about the other neurocognitive affinities such as balance, opposition, etc.? These neu-
Element RefersTo Token

Position
Contain

Unpatterned Respective Relative
Clause
Position Position Position

Precedes
Follows
Initial Medial Final

Figure 8: Classes and relations of Clause and Position

"all" Token "one"

RefersTo RefersTo RefersTo RefersTo

position position position position
rep1e1 rep1e2
(rep1e1) (rep1e2) rep2e1 rep2e2
(rep2e1) (rep2e2)

Element
Element
Of
Of

Element Element
rep1 revRep1 rep2
Of Of

Reversed
Repetition Repetition
Repetition

Before
Before

Before After

Figure 9: Example of Reversed Repetition using Example 1

rocognitive affinities are the results of multiple rhetorical figures working together [26]. In the
scope of Ploke, they are certainly contributed by the subclasses of Repetition. A Clause-Medial
Repetition contributes to balance, a Clause-Boundary Repetition contributes to opposition, a
Reversed Repetition together with a Clause-Medial Repetition contribute to both balance and
opposition, etc. In the case of Example 1, the combination of antimetabole and mesodiplosis
produces a stronger balance. Thus, the forms of plokes do not trigger balance and opposition
directly, but contribute through combinations of Repetition and Position and their subclasses.
That is, repetition and position are the primary neurocognitive affinities triggered by the form
of a ploke.
5. Conclusion and Future Work
We have proposed an ontology for ploke which treats ploke as a class of figures rather than an
isolated figure. The ontology outlines the subclasses of Ploke which includes rhetorical figures
of lexical repetition such as Anadiplosis, Epanaphora, Antimetabole, etc. The ontology also
models the path of the attentional effect a rhetorical figure has on a receiver. That is, Rhetorical
Figure → Form → Neurocognitive Affinity → Attention Effect as in Figure 1.
Another important contribution of the proposed ontology is the classification and represen-
tation of repetition and position, both are primary neurocognitive affinities triggered by the
form of a ploke. In summary, Anadiplosis triggers the Cross-Boundary Repetition, a subclass
of Repetition in which positions of elements are specified as instances of Relative Position, a
subclass of Position. Similarly, Epanaphora, Mesodiplosis and Epiphora trigger specific types
of repetitions in which positions of the elements, e.g., position(rep1e1) and position(rep1e2),
are instances of classes Initial, Medial, and Final respectively, all of which are subclasses of
Relative Position. As demonstrated by the Antimetabole in Figure 9, reversal is the alternation
of positions of Elements that is part of Reversed Repetition, a subclass of Nested Repetition,
in which the Elements are Repetitions.
All neurocognitive affinities triggered by forms of plokes harmoniously generate attentional
effects such as salience, aesthetic pleasure, and increase memorability. Therefore it is crucial to
have a formal knowledge representation model for ploke that includes concepts of neurocogni-
tive affinities in order for AI/NLP systems to take advantage of rhetorical information embedded
in rhetorical figures. The next step is to extend and construct ontologies for other rhetorical
figures, including other schemes, phonological and morphological figures, in similar manner. It
is also possible to incorporate the proposed ontology with existing rhetorical figure detection
tools [5][6][7][19] and other existing rhetorical figures ontologies [10][11][13][14][16][21] to
facilitate NLP applications such as argumentation mining and authorship attribution, etc. For
example, Strommer [6] classified whether an epanaphora is accidental or intentional and used
the result as a metric of author’s intent. The ontology in this paper is a potential extension to
such a system by connecting detection results as instances of classes defined in the ontology,
e.g., repeated words or phrases are instances of Element. All other rhetorical information can
be automatically inferred, which in turn can facilitate the classification of intentionality.
Another possible direction of research is to explore the connection between neurocognitive
affinities and the function of a rhetorical figure. We have already expressed a number of functions
of ploke in First Order Logic. For example, in Figure 9, the proposed ontology is able to infer
that an arbitrary relation 𝑅 exists between the elements rep1e1 and rep2e1 of the Reversed
Repetition, triggered by the form of an Antimetabole, whose function is to convey a reciprocal
relation. However, contextual information is required to instantiate 𝑅. Because functions of
rhetorical figures are loosely researched in the field of rhetoric, it would greatly benefit the field
if the connection between neurocognitive affinities and functions can be established formally.
New discoveries of functions will return the favor to Computational Rhetoric and AI/NLP
with potential rhetorical figure ontologies that are more comprehensive and robust. We also
proposed that repetition and position are the primary neurocognitive affinities that contribute
to other compound affinities such as balance and opposition. We are interested in the formal
representation of how each variation of repetition contributes to the compound neurocognitive
affinities. Therefore, formalizing the connections between these neurocognitive affinities is
another research direction in future.

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