SUGISAKAMASANORI

Journal of Robotics, Networking and Artificial Life
Vol. 9(2); September (2022), pp. 99–114
ISSN (Online):2352-6386; ISSN (Print):2405-9021
https://alife-robotics.org/jrnal.html

Research Article

Implementing the Story Units of Japanese Folktales by Using a
Verb Conceptual Dictionary
Takashi Ogata1, Jumpei Ono2

Faculty of Software and Information Science, Iwate Prefectural University, Sugo 152-52, Takizawa, Iwate, Japan
Faculty of Software and Information Technology, Aomori University, Seishincho 2-10-1, Edogawaku, Tokyo, Japan

1
2

ARTIC LE INFO
Article History
Received 25 November 2020
Accepted 22 April 2022

Keywords
Narrative generation systems
Story unit
Types of folktales
Verb conceptual dictionary

ABSTRACTThis paper deals with the theme of the development of story units based on Japanese folktales.
Each story unit functions in an Integrated Narrative Generation System (INGS), which is the coreof our systematic narrative generation study. In this research framework, story units can bepositioned as a story technique that generates and expands a story structure in the narrative
generation process. This paper focuses on the combination of story units implemented by
Common Lisp using a verb conceptual dictionary, which is important for a noun conceptual
dictionary in conceptual dictionaries functioning in the INGS. The mechanism enables
organically combined processing with other narrative techniques and the use of semantic
functions using conceptual dictionaries functioning in the INGS.

© 2022 The Author. Published by Sugisaka Masanori at ALife Robotics Corporation Ltd
This is an open access article distributed under the CC BY-NC 4.0 license(http://creativecommons.org/licenses/by-nc/4.0/).

“functions” of collected folktales, which are related to themain actions of the main characters in a narrative genre
including a number of Russian folktales. In our narrative
generation systems, we used Propp’s narratologicaltheory as a story generation function [4]. Further, ournarrative generation systems are integrated into an
Integrated Narrative Generation System (INGS) [5].
Before we enter into a concrete discussion of the
topic in this paper, we refer to the research context of thestudy. First, concerning the narrative generation studies
regarding recent narratology, Dawson and Mäkelä [6]have presented narratology’s newest situation. Theirbook contains various themes beyond traditional
narratology, including topics related to information
technologies such as SNS and computer games. The
section on complex systems contains a paper regarding
narrative generation and post-narratology by Ogata [7].
Books that focus more directly on post-narratology [8, 9]

1. INTRODUCTION
A characteristic of our narrative generation study is tointroduce “narratology” as the basis of the theory andimplementation. As Ogata [1,2] proposed, narratology isa literary research area that deals with the structure,generation, distribution, etc. of narrative phenomena in a
broad sense. Although narratology includes a number of
topics and themes, the folktale study discussed in thispaper also forms an important part of narratology. In
addition, Ogata [2] calls the narratology that was
renewed through the introduction of artificial intelligenceand cognitive science “post-narratology.”
For example, in the morphology of folktales [3],Propp collected Russian folktales called magicalfolktales to structurally analyze the tales in terms ofcommonalities found among the collected stories, and hecalled common and abstract event elements seen in the
Corresponding Author’s E-mail: t-ogata@iwate-pu.ac.jp, j.ono@aomori-u.ac.jp

99

simple description that represents its summarized event.
According to Ozawa [42], a motif is a unit that contains
one major action of a major character in the compositionof a story, as well as actions that directly correspond tothat action. To analyze Aarne-Thompson’s International
Folktale Abstracts, it was noted that there weredifferences in the characters and actions of the different
categories of folktales in the International Folktale
Abstracts.
Keigo Seki, a Japanese folklorist, and his groupconducted a survey and analysis of Japanese folktales todraw a comparison with the above research to present asystematic categorization of the “types” of Japanesefolktales [43]. Although the types are similar to themotives in the above research, in that they show asummarized description of each categorization offolktales, many types provide a longer and more complex
description of events for each categorized group of
folktales.
We have presented an idea in which we formalize
the folktale types provided by Seki and his group as theCommon Lisp programs called “story units,” in order toincorporate them into the INGS [44]. However, this study
was incomplete in terms of problems such as thediscordance of the numbers between the original types offolktales and described story units, and development via
the use of an arbitrary method. The main objectives of theabove study are: to complete each formal description of
the story units based on the original texts of Japanesefolktales’ types and combine conceptual elements in thedefined story units with the verb and noun conceptual
dictionaries of the INGS. Through the latter mechanisms,
the story units acquire the ability that is organizationallycombined with the various narrative techniques in the
INGS and enable automated semantic processing such as
semantic linkages among the concepts. In the narrative
generation mechanism found in the INGS, the narrativetechniques, which are central program types, generate
narrative structures in a narrative generation cycle usinga kind of knowledge base, including fragmental narrative
parts. All the narrative techniques and knowledge areorganically and mutually combined with several types ofconceptual dictionaries.
Based on the previous considerations andexperiments [44], this paper defines story units based on
the original texts of all the Japanese folktale types andcombines the verb concepts in story units with the verb

include papers pertaining to the generative models of
language and narrative in broad platforms such as
metaphors [10], poems [11,12], dajare (puns) [13], video
games
[14],
mentalrepresentations[15,16],
advertisements [17,18], movie films [19,20], haiku [21],and business plans [22].
Concerning the computational approach to narrative
as a part of the current narratology, Routledge
Encyclopedia of Narrative Theory [23] contains thesection of “Artificial Intelligence and Narrative” (NichMontfort). Living Handbook of Narratology [24] treats“computational narratology” [25], “story generator
algorithms” [26], “narrativity of computer games” [27],etc. Propp not only deals with the aspects of the story, butalso with a variety of aspects in the narrative. Approaches
have already been proposed to introduce his theories in
the form of narrative generation [28,29,30,31,32,33].
There are studies of narrative generation using
conceptual dictionaries and ontologies. For example,
although the story generation system by Okada and Endo[34] is organized as the application of a relatively largescale conceptual dictionary, the range of themes treatedby it is small. While Mizoguchi [35] has explored themethod of the ontology of Genji Monogatari (The Tale ofGenji), it has not been implemented. Takeuchi [36] hasproposed a conceptual dictionary framework that can beapplied to narratives. Synthetic narrative generation
mechanisms have been proposed and discussed inrelation to knowledge representation [37,38,39]. A
direction for future narrative generation research will beformed by strengthening the basic structure of narrative
generation via the use of richer narratological knowledge,
methods, and techniques, and unifying new methods oflinguistic processing and neural processing, among
others.
The above Propp theory is aimed toward the abstract
and general modeling of the narrative structure offolktales. In contrast, in the same folktale study, there arestudies that treat many folktale examples at a more
concrete level or level of lower abstraction than the Propp
theory. For instance, Aarne and Thompson collected
folktales mainly from various parts of Europe andproduced the International Folk Tale Abstracts [40,41](compiled by Aarne and expanded and revised byThompson, thus, it is called the Aarne-Thompson typeindex [AT index]). It is a classification of themes ofEuropean folktales, and each theme called “motif” has a
100

In addition, these three large categories have“divisions” that group folktales in accordance with theirmotifs, with 11 divisions for “Animal Folktales,” 16 for“Ordinary Folktales,” and 12 for “Joke and Anecdotes”(a total of 39 divisions). In each category, 825 types offolktales were assigned. A total of 825 types of folktales
belong to one of the divisions, each of which contains aminimum of two and a maximum of 66 types of folktales.
Figure 1 is an example of the original text and a
description of a type of folktale. The description and ourpresented program codes, namely story units, are written
only in Japanese, with the related texts also using
Japanese as the basic language. We present an English
translation in this paper for the convenience of thereaders.

conceptual dictionary of the INGS in order for one to beable to use story units as a group of story techniques in
the INGS. In particular, we conducted a survey andanalyzed the description of the types of folktales andautomatically transformed all types of story units into
Common Lisp codes based on our previous attempt. Next,
although we attempt to combine all the verb concepts inthe story units with the verb conceptual dictionary basedon the defined program codes of story units, wecategorize the types of combinations into a simple
combination and more difficult combinations, for which
various special techniques are necessary. Finally, we
present several incomplete points for the future work
toward more comprehensive research, including therevision of the definition of story units and the
combinations of the story units with the verb conceptual
dictionary and other conceptual dictionaries such as noun
and adjective conceptual dictionaries.

四七四 鬼の面 [Oni no Men] (cf. AT 八三一)
ある女 （男） が山 （化け物屋敷）で鬼の面をかぶっている。
[Aru on’na (otoko) ga yama (bakemono-yashiki) de oni no
men wo kabutte iru.] 化け物がそれを見て逃げる。
[Bakemono ga sore wo mite nigeru.] 女は (a) 宝物をとって帰る、または (b) 化け物屋敷の主人になる。[On’na ha (a)takaramono wo totte kaeru, mata ha (b) bakemono-yashiki noshujin ni naru.](474 Demon’s Mask (cf. AT 831)
A woman (man) puts on a demon’s mask in a mountain (amonster house). A monster looks at the mask and runs awayfrom the woman. The woman (a) takes the treasure and goes
home, or (b) becomes a host of the monster house.)
Figure 1. Example of the original description of a type offolktale.

2. TYPES OF JAPANESE FOLKTALES
Seki and his research group structurally analyzed
approximately 35,000 folktales collected from various
areas of Japan. The results were collected in Nihon
Mukashibanashi Taisei (The Complete Collection ofJapanese Folktales) [43,45,46,47,48,49,50,51,52,53,54,55]. This complete collection has a total of 12 volumes.
OF these, volumes 1 to 10 contain the collected folktales,
volume 11 contains materials on the types of folktales, anindex, and a bibliography, and volume 12 contains thecontributed articles on folktales. The study presented inthis paper is related to the types of folktales in volume 11.
In volume 11, Seki and other researchers distributed 825
types of folktales under 39 categories as a classificationof Japanese folktales.
Each type of folktale in the description of the bookcontains a summary of the contents of folktales
corresponding to the type. These types of folktales are
systematized, with the largest categories being 「動物昔話 [Dōbutsu Mukashibanashi]」 (“Animal Folktales”),「本格昔話 [Honkaku Mukashibanashi]」 (“Ordinary
Folktales”), and 「 笑 話 [Shōwa] 」 (“Joke andAnecdotes”), which are based on the AT index. The
animal folktales are tales in which one or more animals
are main characters. The ordinary folktales mean acategory of folktales that narrate the lives of ordinary
humans. The joke and anecdotes are simple tales to makepeople laugh.

3. FORMALIZING THE TYPES OF
JAPANESE FOLKTALES AS STORY UNITS
In this section, we systematically describe the abovementioned survey and analysis of the types of Japanesefolktales to transform them into Common Lisp codes, as
story units. Although our previous study [44] wasconducted based on the Lisp code description, we
attempted it based on the precise and detailed
reconsideration of the original texts of the types offolktales and formalization.
3.1 The Structure of a Folktale Type
Table 1 presents the structural description of Figure 1
based on the format we developed in this study, which
includes the following seven items:
101No.: The serial number for each type of folktales,
based on Seki, Nomura, and Ōshima [43]. For

Table 1. Example of the event structure of a folktale type.
No.

474







Type
Name

鬼の面
[Oni noMen(Demon’sMask)]

Selective
Structure-

Original Text

ある女(男)が山(化け物屋敷)で鬼の面をかぶっている。化け物がそれを見て逃げる。女は (a) 宝
物をとって帰る、または(b) 化け物屋敷の主人になる。 (A woman (man)puts on a demon’s mask
in a mountain (a monster
house). A monster looks
at the mask and runs awayfrom the woman. The
woman (a) takes thetreasure and goes home,or (b) becomes a host of
the monster house.)

instance, in the example of Figure 1, 「四七四[yonhyaku shichijū shi]」 means 474.
Type Name: The original name representing thecharacteristics of folktales is described. 「鬼の面[Oni no Men]」 in Figure 1 means “Demon’s Mask.”
AT Index: The number corresponding to a motif in
the AT index. Some folktales do not havecorresponding numbers. In Figure 1, 「cf. AT 八三
一 [happyaku sanjū ichi]」 means “cf. AT 831.”
Selective Structure: This presents the structure of
the entire type of folktale. In particular, an entire
folktale type can be divided into several exclusive“or” parts in accordance with this selective structure.
For example, 「百足と蛞蝓の旅行 [Mukade to
Namekuji no Ryokō]」 (“Travel of a Centipede andSlug”) (No. 41) is divided into two parts, namely A
and B. They are shown in the following actual
description: 「A 1. 百足と蛞蝓とが旅行し、百足が先に着く [Mukade to namekuji to ga ryokōshi,mukade ga saki ni tsuku]。 2. 蛞蝓は遅れてい
く [Namekuji ha okurete iku]。 百足はまだ十八足草鞋を 脱ぎ残 して いる [Mukade ha madajūhassoku waraji wo nuginokoshite iru]。 B 1. 百足と蛞蝓が旅行を約束し、迎えに行くと百足は草鞋を作っているので蛞蝓は先に行く

Event

ある女（男）が山（化け物屋敷）で鬼の面をかぶっている。 (A woman (man)puts on a demon’s mask ina mountain (a monster
house.)ある女（男）が山（化け物屋敷）で鬼の面をかぶっている (A woman (man)puts on a demon’s mask
in a mountain (a monster
house)
化け物がそれを見て (Amonster looks at themask)（化け物が）逃げる (Amonster) runs away fromthe woman)
女は宝物をとって (Thewoman takes thetreasure)（女は）帰る (Thewoman) goes home)

化け物がそれを見て逃げる。 (A monster looks at
the mask and runs awayfrom the woman.)

Or





102

Sentence

女は (a) 宝物をとって帰る、 (Thewoman (a) takes thetreasure and goes
home,)または (b) 化け物
屋敷の主人になる。 (or (b) becomesa host of themonster house.)（女は）化け物屋敷の主人になる (The woman
becomes a host of themonster house)[Mukade to namekuji ga ryokō wo yakusokushi,
mukae ni yuku to mukade ha waraji wo tsukutte iru
node namekuji ha saki ni yuku]。 2. 蛞蝓は旅か
ら帰ってくるが、百足はまだ作り終わっていない[Namekuji ha tabi kara kaette kuru ga,
mukade ha mada tsukuri oete inai]。」 (“A 1. A
centipede and a slug travel and the centipede arrives
first. 2. The slug is late. The centipede takes off
eighteen pairs of sandals. B 1. The slug andcentipede promise to go on a trip, and when the slug
comes to pick the centipede up, since the centipede
is making sandals, the slug goes ahead. 2. While theslug returns from his trip, the centipede has not yet
finished making sandals.”)
Original Text: The original sentences are describedin this section. The above No., Type Name, AT
Index, and Original Text are items that areincluded in the original description [43].
Sentence: The description of each original text isdivided into a unit of sentences. “Or” refers to thebranching structure that has exclusive possibilities.
Different from the above Selective Structure in theentire level of a story, this “or” structure functions
inside a sentence.



Event: Each sentence is divided into one or more
events. An event is a small narrative unit that isorganically structured based on the verb concept. In
many cases, sentences contain several events. When
there is no subject, it is supplemented based on a
speculation in accordance with the context. In the
INGS architecture, events function as one of themost basic units of story generation and othermechanisms.

However, in the case of verbs, a temporary number 1 iswritten after the verb in order to correspond with the verb
concept. In addition, in this figure (and the following
several code descriptions), the description of &sc (suchas (&sc 女[woman])) means that the noun concept
following the &sc shows the range of noun concepts as
an actual concrete value. In particular, the story
generation mechanism in INGS selects a noun conceptfrom the range using the noun conceptual dictionary. For
example, 少女[girl], 妻[wife], 母[mother], etc.
can be selected from 女[woman].
Although the narrative structure of this example iscomparatively simple, the story units include various
complicated structures. For instance, in the case structureof verbs involving a dialogue such as “say,” the content
of the dialogue is inserted directly into the object case. In
this case, the elements of the object case cannot bechanged or expanded without changing the content of thedescription. Therefore, we consider a more flexible useof the story unit by creating a nested structure of events.
For example, in an event, 「門番は褒美を半分よこせという [Monban ha hōbi wo hanbun yokose to iu]。」(“A gatekeeper tells anyone to give half of the reward.”),x in the event corresponding to the frame, 「門番が x を言う [Monban ga x wo iu]。」 (“The gatekeeper tells
anyone x.”), is equal to the event, 「褒美を半分寄越せ[Hōbi wo hanbun yokose]。」 (“do give half of the
reward to the gatekeeper.”). This is because we caninterpret 「寄越せ [yokose]」 (“do give”) as a strong
tone corresponding to 「 命 令 す る [meireisuru] 」(“order”) and this “order” is in the framework of “say.”Moreover, we can regard the object for 「命令する[meireisuru] 」 (“order”) as 「 百 姓 [hyakushō] 」(“farmer”) from the context. Based on the above nested
event,

3.2 Creation of Story Units
We created the story units as Common Lisp programs
based on the “event” descriptions provided in Table 1.
We created 825 story units from 825 folktales.
Technically, all the 825 types are listed in an Excel filein accordance with the form of Table 1, and theframeworks for story units by Common Lisp areautomatically generated. Figure 2 is an example of this.
Subsequently, the case structures in the frameworks were
described by hand. The completed story units are shownin Figure 3.
(motif0669 (鬼の面[demon’s-mask])((ある女(男)が山(化け物屋敷)で鬼の面をかぶっている。)(化け物がそれを見て)(「化け物が」逃げる)(or(女は宝物をとって「女は」帰る)(「女は」化け物屋敷の主人になる。))))

Figure 2. Automatically generated framework of a story
unit.

(event 言う 1[tell](agent (&sc 門番[gatekeeper])(object(event 命令する 1[order](agent (&sc 門番[gatekeeper]))(counter-agent (&sc 百姓[farmer]))(object(event 与える 1[give]

Figure 3 is an example of the story unit that was
created based on the folktale type presented in Table 1.
The branching structure of the type of folktale isrepresented through a description starting with “or,” asshown in Figure 3. In this example, there were five eventsin the story unit. Each event is composed of a verb andits case information based on the way events aredescribed in the INGS. The descriptions of verbs and thecase elements in the story unit are based on thedescriptions provided in the type of folktales. They do notcorrespond with the verb and noun concepts in the INGS.
103

(motif0669 (鬼の面[demon’s-mask] (被る 1[put-on] 見る 1[look] 逃げる 1[run-away] (or (取る1[take] 帰る 1[go-home]) なる 1[become])))((1 (event 被る 1[put-on] (agent (&sc 女[woman])) (object (&sc 鬼の面[demon’smask])) (location (&sc 山[mountain]))))(2 (event 見る 1[look] (agent (&sc 化け物[monster])) (counter-agent (&sc 女[woman]))))(3 (event 逃げる 1[run-away] (agent (&sc 化け物[monster]))))(or(4a(event 取る 1[take] (agent (&sc 女[woman])) (object (&sc 宝物[treasure])))(event 帰る 1[go-home] (agent (&sc 女[woman]))))(4b (event なる 1[become] (agent (&sc 女[woman])) (to (&sc 化け物屋敷の主人[host-of-monster-house])))))))
Figure 3. Example of a story unit.

(agent (&sc 百姓[farmer]))(counter-agent (&sc 門番[gatekeeper]))(object (&sc 褒美の半分[thehalf of reward])))))))In this study, we created 825 story units based on the 825
types of folktales and our detailed description through theautomated generation function drawn from the Excel
description newly coded by Common Lisp. The 558 story
units generated do not have a branch structure, and theremaining 267 story units have a branch structure. 27
story units in the 267 units have a branch structure basedon Selective Structure. In particular, the 19 story unitsof the respective 27 units only have a Selective
Structure. These story units have 72 events at most, andone event in the smallest case. Approximately 90 % of
the story units have 20 or fewer events. There was a totalof 55 story units with more than 21 events. There were
only 2 story units with more than 50 events.

is described.
Among the case elements of the story units, there
are 766 cases that can be nested. Table 2 presents theclassification of the nested structures based on our
analysis. In this table, Example shows an example of anested event, and the boldfaced type corresponds with theinside event. Structure presents a description of a nested
event transformed from the sentence of the Example. A
total of 433 nested events were identified. According toour categorization of the nested events and the analysisof the semantic structures, we defined the methods ofmaking a nested event for the 9 classifications as
indicated in Table 2.
Although the verb concept is directly used in “Anaction” and “Actions” to make the nested event, withregard to Avoidance to Desire, the following verb
concepts are used instead of the original verb concepts:「回避する [kaihisuru]」(“avoid”) (Avoidance), 「禁止する [kinshisuru]」(“prohibit”) (Prohibition), 「提案する [teiansuru]」(“propose”) (Proposition), 「話す[hanasu] 」 (“speak”) (Speech), 「 命 令 す る[meireisuru ] 」 (“order”) (Order), and 「 望 む[nozomu] 」 (“desire”) (Desire). In the case of Hearing,「 聞く [kiku]」 (“hear”) is used directly.

4. COMBINING STORY UNITS WITH A
VERB CONCEPTUAL DICTIONARY
We combined the story units with a verb conceptual
dictionary in the INGS. This section first proposes a
simple explanation of the verb conceptual dictionary,followed by the concrete combination method of story
units and the verb conceptual dictionary. Refer toreference [56] concerning a conceptual dictionary
including a verb conceptual dictionary and otherconceptual dictionaries in the context of our narrative
generation research.

3.3 Implementation Result
As stated in the first part of Section 3, in this paper, we
revised the previous implementation of story units [44].

104Category

ActionActions

Avoidance

Prohibition

Proposition

Speech

Order

DesireHearing

Total

Meaning

Table 2. Nested event structures in story units.
ExampleEvent Representation

246

An event
structure
consistingof a single
action.

嫁が、猫が踊っているのを発見する。
[Yome ga, neko ga odotte iru no wo
hakkensuru.] (A wife finds a cat
dancing.) (No. 255, 猫の踊 [Neko no
Odori] (Cat’s Dance))(event 発見する 1[find] (agent (&sc 嫁[wife]))(object (event 踊 る 1[dance](agent(&sc 猫[cat])))))

50

An event
structure
consistingof multiple
actions.

親 父 は 飲 ん で 賢 く な っ た と 答え る 。
[Oyaji ha nonde kashikoku natta tokotaeru.] (My dad replies that he drinks
a drag and becomes a wise man.) (No.
521, 殿様と小僧 [Tonosama to Kozō](A Load and Child))1

An event
structurein which a
certainaction is
avoided.

吉四六は感染せぬようにして垣を作る[Kicchomu ha kansen senu youni shite
kaki wo tsukuru.] (Kicchomu makes ahedge so that he does not get infected.)(No. 613, 隣の喧嘩 [Tonari no Kenka](A Quarrel of Neighbors))

15

An event
structurein whichcertainactions areprohibited.

男は地蔵にこのことを他言するなという。[Otoko ha jizō ni kono koto wo tagon
suruna to iu.] (A man told a jizō not totell anyone about this thing.) (No. 本格
新 33 [Honkaku-shin 33] (Ordinary
folktales, new, 33) こんな晩 [Kon’naBan] (Such Night))

10

An event
structurein whichan actionis
proposed.

助け合おうと約束する。[Tasuke aou toyakusokusuru.] (We promise to help
each other.) (No. 動物新 20 [Dōbutsushin 20] (Animal Folktales, new 20), 獅
子といるか [Shishi to Iruka] (A Lionand Dolphin))5

An event
structurein which acharacterspeaksanything.

猿 は 生 肝 を 忘 れ た と い う [Saru haikigimo wo wasureta to iu.] (A monkey
tells that he forgot to bring his liver)(No. 35, 猿の生肝 [Saru no Ikigimo](The Heart of a Monkey))68

An event
structurein whichan actionis ordered.

門番は褒美を半分よこせという[Monban ha hōbi wo hanbun yokose toiu.] (The gatekeeper tells to anyone to dogive the half of reward.) (No. 笑話新 11[Shōwa-shin 11] (Joke and Anecdotes,
new 11), 拳 骨 の 褒 美 [Genkotsu no
Hōbi] (A Reward of Punches))

33

An event
structurein whichan action
is wanted.

漁夫（樵夫）が妻を得たいと神に祈願する[Gyofu (shōfu) ga tsuma wo etai tokami ni kigansuru.] (A fisherman(woodcutter) prays to the god to get awife.) (No. 118, 天 人 女 房 [Ten’nin
Nyōbō] (Heavenly Bride))5

An event
structurein which acharacterhears
anything.

神々が男の嫁を決めたのを聞く[Kamigami ga otoko no yome wo kimeta
no wo kiku]。 (Hearing that the gods
have decided on a man's wife.) (No. 本
格新 30 [Honkaku-shin 30] (Ordinary
folktales, new 30), 夫婦の縁 [Fūfu noEn] (Fate Between a Husband and Wife)

105(event 答える 1[reply] (agent (&sc 親父[dad]))(counter-agent(&sc
侍[samurai])) (object ($継起 (event 飲む
1[drink] (agent (&sc 子 供 [child]))(object (&sc 薬 [drag])))(event な る
1[become] (agent (&sc 子 供 [child]))(object (&sc 賢い[wise]))))))(event 作る 1[make] (agent (&sc 吉四六[Kicchomu])) (object (&sc 垣[fence]))(purpose (event 回避する 1[avoid] (agent(&sc 吉四六[Kicchomu])) (object (event
感 染 す る 1[infect] (agent (&sc 吉 四 六[Kicchomu])) (object (&sc 夫 婦 喧 嘩[conjugal quarrel])))))))(event 言う 1[tell] (agent (&sc 男[man]))(counter-agent(&sc
地 蔵 [Jizo]))(object (event 禁 止 す る 1[prohibit](agent (&sc 男 [man])) (counter-agent(&sc 地蔵[Jizo])) (object (event 言う
1[tell] (agent (&sc 地 蔵 [Jizo]))(object (&sc このこと[this thing])))))))(event 約束する 1[promise] (agent (&sc ラ
イオン[lion])) (counter-agent (&sc いるか[dolphin])) (object (event 提 案 す る 1(agent (&sc ラ イ オ ン [lion])) (object(event 助け合う 1[help each other] (agent(&sc ラ イ オ ン [lion])) (counter-agent(&sc いるか[dolphin])))))))(event 言 う 1[tell][monkey])) (object
1[forgot to bring][monkey])) (object
liver])))))(agent (&sc 猿(event 忘 れ る(agent (&sc 猿(&sc 生 肝 [raw（ event 言 う 1[tell] (agent (&sc 門 番[gatekeeper]) (object (event 命 令 す る
1[order] (agent (&sc 門番[gatekeeper]))(counter-agent (&sc 百 姓 [farmer]))(object (event 与える 1[give] (agent (&sc
百姓[farmer])) (counter-agent (&sc 門番[gatekeeper])) (object (&sc 褒美の半分[the half of reward])))))))(event 祈願する 1[pray] (agent (&sc 漁夫[fisherman])) (counter-agent (&sc 神[god])) (object (event 望む 1 (agent(&sc 漁夫[fisherman])) (object (event
得る 1[get] (agent (&sc 漁夫[fisherman]))(object (&sc 妻[wife])))))))(event 聞く 1[hear] (agent (&sc 男[man]))(object (event 決める 1[decide] (agent(&sc 神々[gods])) (object (&sc 男の嫁[man’s wife])))))

4.1 Overview of a Verb Conceptual Dictionary

units and implemented the methods in accordance to theclassification.
The 825 story units that we created had 1,117
different verbs. These verbs can be divided into those thatcan be easily combined with the verb conceptual
dictionary and those that require some work to be donein order to be combined with the verb conceptual
dictionary. First, we classified the verbs in the story unit
in terms of the challenges in binding. Table 3 presents thebreakdown of the classification, the number of units
corresponding to the category, and a concrete example ofthe category.
The verb concepts in A (“Direct Connection”)
directly exist in the verb conceptual dictionary. In
contrast, the verb concepts from B to E (“NewRegistration,” “Notation,” “Passive Form,” and“Negative Form”) do not have the corresponding verb
concepts in the verb conceptual dictionary. In thefollowing section, we explain all of these categories.

A “concept” here is a datum that shows the meaning andclassification of a word. A conceptual dictionary that
stores many concepts is an ontology of words in the
INGS. The entire conceptual dictionary is a collection oflower-level conceptual dictionaries. A verb conceptual
dictionary and a noun conceptual dictionary are the mostrepresentative conceptual dictionaries, and there areother dictionaries, including adjective and adjective verb
conceptual dictionaries. The verb conceptual dictionary
systematically registers 11,951 verb concepts, and thenoun conceptual dictionary is a systematic dictionary ofnoun concepts, including 115,765 general noun concepts.
There is also the existence of a proper noun conceptual
dictionary.
Figure 4 presents an example of a verb concept. As
shown in this example, a verb concept has a “sentence
pattern,” a “case frame,” and a “constraint.” A sentence
pattern describes the most basic and simple sentence
form in the transformation, which ranges from an event
representation to a surface language representation. A
case frame is a descriptive form that defines the types ofconcepts required semantically by a verb concept.
Constraint describes the constraints for selecting a caseframe from the noun concept dictionary, and “is-a” pieceof information for systematically classifying the verbs.
When each verb concept in the defined story units is
combined with the corresponding part in the verb
conceptual dictionary, the above functions are effectively
used to organize and expand the possibility of narrative
generation and representation.

A. Direct connection
The verb concepts of this group in the described story
units are directly combined with the verb concepts in theverb conceptual dictionary.
Each verb concept in the dictionary is defined using
the verb stem, and a typical notation form as a verb
notation has various possibilities in Japanese. The verb
concepts in A are equal to those in the dictionary.
However, it is necessary to adjust the verb number for a
specific verb concept in accordance with the differencein the meanings indicated by the verb concept. For
instance, a Japanese verb concept, 「食べる [taberu]」(“eat”) has several different meanings, such as “earn” and“eat.” Since our verb conceptual dictionary respectively

4.2 Method for the Combination of Story Units
with a Verb Conceptual Dictionary
We organized the types of verbs contained in the story(set'通行する 1[pass-through] '((name 通行する 1[pass-through])(sentence-pattern "N1 が N2 を 通行する"[“N1 pass through N2”])(case-cons-set((case-frame ((agent N1) (location N2)))(constraint ((人[human] -死人[corpse] -人間〈人称〉[human<person>] -準人間[semi-human])(場所[location] -世界[world] -景[view] -宇宙[space] 建造物[building] -屋
根[roof] -柱・梁〔はしら・はり〕 [pillar / jo4ist] -壁[wall] -家屋{部分〈要素{その他}〉}{アンテナ }[building{parts<element{etc.}>}{antenna}] - 家 屋 { 部 分 〈 要 素 { そ の 他 } 〉 }{ 避 雷針}[building{parts<element{etc.}>}{lightning-rod}] -建具[fixture] -塀[fence])))))(is-a (v 物理的移動 [physical-movement]))))
Figure 4. Example of a verb concept.

106

of the target verb in the story unit. The sentence patternis created by specifying the particle corresponding toeach case used in the case frame and combining the “casenumber” and the “particle corresponding to the case.” In
the tentative data, we did not provide any constraints on
the cases to be used, and all “is-a” to classify the verb
types were set for “physical action.” In this example, thecases registered in the original story unit are the agent
case, which represents the subject, and the object case,which represents the object.

Table 3. Categories of combination methods
between the verb concepts in story units andthe verb conceptual dictionary.
CategoryA.

Total
NumberC.

DirectConnection
New
Registration
Notation

D.

Passive Form

13

E.

Negative
Form

5

B.

Total

615
363
121

Example食べる [taberu] (eat)あさる [asaru](scavenge)
気づく [kizuku] (notice)
追われる [owareru] (bechased)承知しない[shōchishinai] (notagree)

C. Notation
The notation of the verb concepts included in this groupcan be changed in accordance with the corresponding
verb concepts in the dictionary. For instance, the notationof 「気 づく [kizuku] 」(“notice”) in a story unit ischanged to 「気付く [kizuku]」(“notice”), which is thecorresponded notation used in the verb conceptual
dictionary.

1,117

describes them as 「食べる 1」 and 「食べる 2」, thestory units are necessary to reflect this mechanism.
Here, we refer to the processing of sentence
generation by natural language based on the story units.
This is done using the natural language generation
mechanism contained in an INGS. For verb concepts thathave the same notation, once the description of the story
unit is used as it is, the sentence generation mechanismof INGS is used to expand the sentence into a naturalsentence, and if a natural sentence that matches thecontent of the story unit is expanded, it is used as it is. Ina situation of no case, we select an appropriate verb
concept number from the verb concept dictionary andchange the number of story unit verbs to that number.
Currently, all the created story units can be automaticallytransformed to natural language sentences.

D. Passive form
The verb concepts in this category are described inpassive forms. With regard to group D, we changed eachverb concept to the verb stem and assigned a concept
number to the concept. Furthermore, the alteration fromthe passive to positive is conducted through theadjustment of the contents in the “agent” and “counteragent” cases present in the story unit. For example,(追われる 1 [be chased](agent A) (counter-agent B))

B. New registrationis altered toSince the verb concepts in this group do not exist in theverb conceptual dictionary, we need to register them inthe dictionary.
With respect to the verb concepts in B, we firstcheck to see if there are any verb concepts that have thesame meaning but different notations in the verb concept
dictionary, and if so, we process them as the task in C. If
there is no verb with a different notation, we register it asa new verb concept in the verb concept dictionary. For
each new verb, we created a sentence pattern and a caseframe based on the case structure of the target verb in thestory unit. Case-frame refers to the case structure of theverb in the story unit, and the case frame refers to the case(追う 1 [chase](agent B) (counter-agent A)).
E. Negative form
The verb concepts in this category are described innegative forms. The verb concepts belonging to category
E is firstly altered for the verb stem and “not” is added to
the verb concept for representing negative meaning. For
example,(event 承知しない 1[not agree](agent A) (object B))
107

(event なる 1[become](agent (&sc 女[woman]))(to (&sc 化 け 物 屋 敷 の 主 人 [host-ofmonster-house])))is described as(event (not 承知する 1[agree])(agent A) (object B)).”

based on “B. New Registration.”
Figures 5, 6, 7, 8 and 9 present the generated
examples of story units and the original description [43]in accordance with the above A to E. However, this is atentative accomplishment as the investigation of theresults has not been conducted. In the next section, we
discuss theF. Current situation of the combination
In this study, we combined all the verb concepts in thecreated story units with the verb concepts in the verb
conceptual dictionary in accordance with the above
methods. For example, in the example of a story unit
shown in Figure 1, the used verb concepts are based on
Story
Unit

Original
Text(motif0436 (物いう魚 [Talking fish] (or (捕らえる 1[catch] 持ち帰る 1[return] 聞こえる
1[hear] (or 答える 1[reply] する 1[do]) 驚く 1[surprise] 放す 1[release]) (拾う 1[pick]
かける 1[hang] 聞こえる 1[hear] 返しに行く 1[return] 会う 1[meet] やる 1[give] 食べる 2[eat]来る 1[come] 流される 1[sweep])))
(or
(($継起
(1 (event 捕らえる 1[catch] (agent (&sc 男[man])) (object (&sc 魚[fish]))))(2 (event 持ち帰る 1[return] (agent (&sc 男[man])) (object (&sc 魚[fish]))))(3 (event 聞こえる 1[hear] (object (&sc 声[voice])) (from (&sc 淵[pond]))))(or(4a (event 答える 1[reply] (agent (&sc 持っている魚 [had fish]))))(4b (event する 1[do] (agent (&sc 捕まえた魚 [caught fish])) (object (&sc 話[talk])))))(5 (event 驚く 1[surprise] (agent (&sc 男[man]))))(6 (event 放す 1[release] (agent (&sc 男[man])) (object (&sc 魚[fish]))))))(($継起(A(1 (event 拾う 1[pick] (agent (&sc 男 1[man])) (object (&sc 魚[fish]))))(2 (event かける 1[hang] (agent (&sc 男 1[man])) (object (&sc 魚[fish])) (to(&sc 軒[eaves])))))(B(1 (event 聞こえる 1[hear] (agent (&sc 男 1[man])) (object (&sc 一波寄するか……[I will call a tsunami into the house...]))))(2 (event 返しに行く 1[return] (agent (&sc 男 1[man]))))(3 (event 会 う 1[meet] (agent (&sc 男 1[man])) (counter-agent (&sc 男
2[man]))))(4 (event やる 1[give] (agent (&sc 男 1[man])) (counter-agent (&sc 男 2[man]))(object (&sc 魚[fish])))))(C(1 (event 食べる 2[eat] (agent (&sc 男 2[man])) (object (&sc 魚[fish]))))(2 (event 来る 1[come] (object (&sc 大津波 [big tsunami]))))(3 (event 流される 1[sweep] (agent (&sc 男 2[man])))))))))
A 1. 男が魚（やまめ・山椒魚・池淵の主・鰻）を捕える [Otoko ga sakana (yamame, sanshōuo, ikenofuchi no nushi,
unagi) wo toraeru]。2. (a) 持ち帰ろうとすると淵から声がする [Mochikaerou to suru to fuchi kara koe ga suru]。持っている魚がそれに答える [Motte iru sakana ga sore ni kotaeru]。 (b) 捕えた魚が話しをする [Toraeta sakana ga
hanashi wo suru]。 3. 男は驚いて放す（捨てて逃げる） [Otoko ha odoroite hanasu (suttee nigeru)]。 B 1. 魚を拾って軒にかけておく [Sakana wo hirotte noki ni kakete oku]。 2. 「一波寄するか……」と声がするので返しに行くと途中で男に会い、魚をやる [“Hitonami yosuruka ……” to koe ga suru node kaeshi ni yuku to tochū de otoko ni ai,
sakana wo yaru]。 3. 男が食べると大津波が来て流される [Otoko ga taberu to ōtunami ga kite nagasareru]。(A 1.
A man catches a fish (oncorhynchus, salamander, the lord of Ikenofuchi, eel). 2. (a) The man hears a voice from apond when the man returns home with the fish. The fish the man has replies to the voice. (b) The fish that the mancaught speaks. 3. The man is surprised and releases the fish (the man throws the fish and runs away). B 1. A person
picks up a fish and hangs it on an eaves. 2. The person returns the fish because the person hears a voice that “I willcall a tsunami into the house...” and the person meets a man at half-way and gives the fish to the man. 3. The man eats
the fish, a big tsunami comes, and the man is swept by the big tsunami.)
Figure 5. Example of a story unit and an original description in “A. Direct Connection.”“A. Direct Connection,” except for108

StoryUnit

Original
Text

Story
Unit

Original
Text(motif0650 (栃まなこ [Eyes of Japanese horse-chestnut] (落とす 1[drop] 入れる 1[fit] 見える
1[look] なる 1[become] (or 入れる 1[fit] 入れる 1[fit]) あさる 1[scavenge] 食べる 2[eat]))((A(1 (event 落とす 1[drop] (agent (&sc 男[man])) (object (&sc 目玉[eye ball]))))(2 (event 入れる 1[fit] (agent (&sc 男[man])) (object (&sc 目玉 [eye ball]))))(3 (event 見える 1[look] (agent (&sc 男[man])) (object (&sc 腹の中 [inside body]))))(4 (event なる 1[become] (agent (&sc 男[man])) (to (&sc 名医 [excellent doctor]))))(or(5a (event 入れる 1[fit] (agent (&sc 隣の男 [man next to him])) (object (&sc 栃の実[conker]))))(5b (event 入れる 1[fit] (agent (&sc 隣の男 [man next to him])) (object (&sc 犬の目[dog’s eye])))))(6 (event あさる 1[scavenge] (agent (&sc 隣の男 [man next to him])) (object (&sc 他人のごみ[other people's garbage heap]))))(7 (event 食べる 2[eat] (agent (&sc 隣の男 [man next to him])) (object (&sc 他人のごみ[other people's garbage heap])))))))
ある男が目玉を落として誤って逆に入れる [Aru otoko ga medama wo otoshite ayamatte gyaku ni ireru]。腹の中がよくみえる
ので名医になる [Hara no naka ga yoku mieru no de meii ni naru]。隣の男がまね て(a) 栃の実または (b) 犬の目を入れる[Tonari no otoko ga manete (a) tochi no mi mata ha (b) inu no me wo ireru]。他人のごみ溜めをあさって食うようになる [Tanin nogomi wo asatte kuu you ni naru]。 (A man drops an eye ball and fits the eye into the eye socket in reverse direction by mistake. The man
becomes an excellent doctor because he clearly looks inside the body. A man next to him mimicked him. The man (a) fits a conker into
an eye socket, or (b) fits a dog’s eye ball into an eye socket. He begins to scavenge and eat from the other people’s garbage heaps.)
Figure 6. Example of a story unit and an original description in “B. New Registration.”(motif0378 (山伏と一軒家 [Yamabushi and solitary house] (おどす 1[scare] 驚く 1[surprise] 落
ちる 1[fall] 暮れる 1[set] 泊まる 1[stay] (or 出る 1[come] うなる 1[groan] (つける 1[dye] 開ける
1[open] 見せる 1[show])) 驚く 1[surprise] 逃げる 1[run away] 落ちる 1[fall] 気づく 1[notice] 笑
う 1[laugh]))(($継起(A(1 (event おどす 1[scare] (agent (&sc 山伏[yamabushi])) (counter-agent (&sc 寝ている狐[fox that slept])) (object (&sc 法螺貝[trumpet shell]))))(2 (event 驚く 1[surprise] (agent (&sc 狐[fox]))))(3 (event 落ちる 1[fall] (agent (&sc 狐[fox])) (to (&sc 川[river])))))(B(1 (event 暮れる 1[set] (object (&sc 日[sun]))))(2 (event 泊まる 1[stay] (agent (&sc 山伏[yamabushi])) (to (&sc 一軒家 [solitary
house]))))(or(3a (event 出る 1[come out] (agent (&sc 死者[dead]))))(3b (event うなる 1[groan] (agent (&sc 病人 [sick person]))))(3c (event つける 1[dye] (agent (&sc 婆 [old woman])) (object (&sc おはぐろ[tooth
blackening])))(event 開ける 1[open] (agent (&sc 婆 [old woman])) (object (&sc 大きな口[bigmouth])))(event 見せる 1[show] (agent (&sc 婆 [old woman])) (counter-agent (&sc 三伏[yamabushi]))))))(C(1 (event 驚く 1[surprise] (agent (&sc 山伏[yamabushi]))))(2 (event 逃げる 1[run away] (agent (&sc 山伏[yamabushi]))))(3 (event 落ちる 1[fall] (agent (&sc 山伏[yamabushi])) (to (&sc 川[river]))))(4 (event 気付く 1[notice] (agent (&sc 山伏[yamabushi])) (object (&sc 日は明るい [dayis bright]))))(5 (event 笑 う 1[laugh] (agent (&sc 人 [people])) (counter-agent (&sc 山 伏[yamabushi]))))))))
1. 山伏が法螺貝で狐をおどすと、狐は驚いて川に落ちる [Yamabushi ga horagai de kitsune wo odosu to, kitsune ha odoroite
kawa ni ochiru]。2. 日が暮れて一軒家に泊まる [Hi ga kurete ikkenya ni tomaru]。(a) 死者が出てくる [Shisha ga dete kuru]。(b)
病人がうなっている [Byōnin ga unatteiru]。(c) 婆がおはぐろをつけて大きな口を開けて見せる [Baba ga ohaguro wo tsukete
ookina kuchi wo akete miseru]。3. 山伏は驚いて逃げて川に落ちる [Yamabushi ha odoroite nigete kawa ni ochiru]。気づくと日は
明るく、人に笑われる [Kizuku to hi ha akaruku, hito ni warawareru]。 (1. A yamabushi, a fox with a trumpet shell, and the fox issurprised and falls into the river. 2. The sun sets and the priest stays at a house. 2. The sun sets and the yamabushi stays at a solitary house.
(a) The dead come out. (b) The sick person is groaning. (c) An old woman dyes a tooth with blackening and opens her big mouth toshow it to the yamabushi. 3. The yamabushi is surprised and runs away and falls into the river. When he notices, the day is bright andthe yamabushi is laughed at by people.)
Figure 7. Example of a story unit and an original description in “C. Notation.”

109

StoryUnit

Original
Text(motif0336 (三枚の護符 [three talismans] ((or 泊まる 1[stay] 追う 1[chase]) 取り替える
1[replace] 投げる 1[throw] できる 1[appear] 投げる 1[throw] できる 1[appear] 投げる
1[throw] できる 1[appear] (or 死ぬ 1[die] (逃げ帰る 1[return] 求める 1[request] する
1[do] 命令する 1[order] 食べる 1[eat] 救う 1[save]))))
(($継起
(A
(or
(1a (event 泊 ま る 1[stay] (agent (&sc 子 供 [child])) (to (&sc 山 姥 の 家[Yamamba's house]))))(1b (event 追う 1[chase] (agent (&sc 山姥[Yamamba])) (counter-agent (&sc 子
供[child]))))))(B(1 (event 取り替える 1[replace] (agent (&sc 子供[child])) (object (&sc 山姥が腰 に 結 び つ け た 縄 [A rope Yamamba tied around her waist])) (to (&sc 護 符[talisman]))))(2 (event 投 げ る 1[throw] (agent (&sc 子 供 [child])) (object (&sc 護 符[talisman]))))(3 (event できる 1[appear] (object (&sc 川[river]))))(4 (event 投 げ る 1[throw] (agent (&sc 子 供 [child])) (object (&sc 護 符[talisman]))))(5 (event できる 1[appear] (object (&sc 山[mountain]))))(6 (event 投 げ る 1[throw] (agent (&sc 子 供 [child])) (object (&sc 護 符[talisman]))))(7 (event できる 1[appear] (object (&sc 火[fire]))))(or(8a (event 死ぬ 1[die] (agent (&sc 山姥[Yamamba]))))(8b (event 逃 げ 帰 る 1[return] (agent (&sc 子 供 [child])) (to (&sc 寺[temple])))(event 求める 1[request] (agent (&sc 子供[child])) (counter-agent (&sc
和尚[monk])) (object (&sc 救い)))(event する 1[do] (agent (&sc 和尚[monk])) (counter-agent (&sc 山姥[Yamamba])) (object (&sc 化け比べ [a contest of the transforming])))(event 命令する 1[order] (agent (&sc 和尚[monk])) (counter-agent (&sc 山姥[Yamamba])) (object (&sc 豆に化ける [turns her into a bean])))(event 食べる 1[eat] (agent (&sc 和尚[monk])) (object (&sc 豆[bean])))(event 救う 1[save] (agent (&sc 和尚[monk])) (counter-agent (&sc 子供[child])))))))))
1. 子供（小僧）が山姥の家に泊まる [Kodomo (kozō) ga yamanba no ie ni tomaru]。または追われる [Mata haowareru]。2. 山姥が腰に結びつけた縄を護符にとりかえる [Yamanba ga koshi ni musubi tsuketa nawa wo gofu ni
torikaeru]。三枚の護符（鏡・櫛・針・玉）を投げて (a) 川（海）・ (b) 山（剣の山）・ (c) 火（藪）をつくって逃げる[Sanmai no gofu (kagami, kushi, hari, tama) wo nagete (a) kawa (umi), (b) yama (tsurugi no yama), (c) hi (yabu) wo
tsukutte nigeru]。3 (a) 山姥は火で焼け死ぬ [Yamanba ha hi de yakeshinu]。または (b) 寺まで逃げ帰り、和尚に救いを求める [Mata ha (b) tera made nigekaeri, oshō ni sukui wo motomeru]。4. 和尚は山姥と化け比べをして豆に化けさせて山姥を食い、小僧を救う [Oshō ha yamanba to bakekurabe wo shite mame ni bakesasete yamanba wo
kui, kozō wo sukuu]。(1. A child (young Buddhist) stays at a yamanba’s house, or is chased away. 2. A child replaces
the rope the yamanba tied around her waist with a talisman. The child throws three talismans (a mirror, a comb, aneedle, and a ball) and escapes by making (a) a river (the sea), (b) a mountain (a mountain of swords), and (c) a fire(a bush). 3 (a) The yamanba is burned to death by the fire. (b) She runs back to the temple and asks the monk to saveher. 4. The monk has a contest with the yamanba and turns her into a bean, which eats the yamanba and saves theboy.)
Figure 8. Example of a story unit and an original description in “D. Passive Form.”

semantic possibilities of these verbs need moreconsideration.
Second, as mentioned in the last part of the previous
section, we did not investigate the results of the
combination mechanism of events in the story units withthe verb conceptual dictionary. A method for conducting
this is to investigate and evaluate the results through anactual computer simulation of the created story units
using the natural language sentence generation or thetransformation mechanism mentioned in the previous

problems, including the investigation and future work ofthis study.
5. DISCUSSION AND FUTURE WORKSFirst, semantic investigations and revisions of the createdstory units are necessary for the qualitative improvementof this study in the future. For example, although we used
several determined verbs for nested events in the current
implementation of story units, the adequacy and other110

StoryUnit

Original
Text(motif0266 (竜神 と釣 [Ryujin and fishing] (借りる 1[borrow] 取 る 1[take] 返 す1[return] 承知する 1[agree] 探しに行く 1[look] 返す 1[return] 返す 1[return]))(($継起(A(1 (event 借りる 1[borrow] (agent (&sc 漁夫[fisherman])) (counter-agent (&sc
友人[friend])) (object (&sc 釣り針[hook]))))(2 (event 取る 1[take] (agent (&sc 魚[fish])) (object (&sc 釣り針[hook])))))(B(1 (event 返す 1[return] (agent (&sc 漁夫[fisherman])) (counter-agent (&sc 友人[friend])) (object (&sc 同じ物 [same things]))))(2 (event (not 承知する 1[agree]) (agent (&sc 友人[friend])))))(C(1 (event 探しに行く 1[look] (agent (&sc 漁夫[fisherman])) (to (&sc 海底 [bottomof the sea]))))(2 (event 返す 1[return] (agent (&sc 竜神[Ryujin])) (counter-agent (&sc 漁夫[fisherman])) (object (&sc 釣り針[hook]))))(3 (event 返す 1[return] (agent (&sc 漁夫[fisherman])) (counter-agent (&sc 友人[friend])) (object (&sc 釣り針[hook]))))))))
1. 漁夫が友人に釣り針を借りて魚にとられる [Gyofu ga yūjin ni tsuribari wo karite sakana ni torareru]。2. 同じものを返そうとするが、友人が承知しない [Onaji mono wo kaesou to suru ga, yūjin ga shōchishinai]。3. 漁夫は海底に探しに行って、竜神に釣り針を返してもらって友人に返す [Gyofu ha kaitei ni sagashi ni itte, ryūjin ni tsuribari
wo kaeshite moratte yūjin ni kaesu]。(1. The fisherman borrows a hook from his friend and a fish takes the hook. 2.
He tries to return the same hook, but his friend doesn't agree. 3. The fisherman goes to the bottom of the sea to look
for the hook and gets the hook back from the ryūjin and returns it to his friend.)
Figure 9. Example of a story unit and an original description in “E. Negative Form.”

section. Moreover, while conducting the experiment in
the current stage is certainly possible, the combination of
the part of noun concepts in the story units with the noun
conceptual dictionary in the INGS is still incomplete. In
order to ensure the efficiency of the study performance,
a better process is to conduct an investigation of thequality of combination following the processing of thenoun concepts.
Third, one of the ultimate objectives of this study is
to use the created story units combined with conceptual
dictionaries for the entire narrative generation processcarried out in an INGS. While a narrative generation
inside a set of story units is possible using various
methods such as synthesis, transformation, and othertechniques of story units, narrative generation throughmutual relationships with diverse story techniques iscarried out in an INGS. In such relationships, the roles
and functions of the story units can be diverse. For
example, there is a story unit that shows the structure ofa large story. However, there is a story unit that shows
the local structure of a story. In addition, the story units
can be used to generate folktale-like stories.
Simultaneously, by combining the story units, it ispossible to create a story that is different from the original
story.
Finally, one of our concrete plans for actual
narrative creation is to write experimental novels or
narratives using generated story units, moreover, byadding the interpretation process ourselves. In particular,

original narrative texts generated through the synthesis,
transformation, etc. of the story units are rewritten basedon further transformation, expansion, precision, and soon. This process refers to the completion of the text
generated via the narrative generation mechanism basedon our interpretation.
6. CONCLUSION
In this paper, we implemented the story units produced
by using Common Lisp through a comprehensive andprecise survey and analysis of the study of the types ofJapanese folktales. Furthermore, all the verb concepts
included in the description of the story units were
semantically combined with the verb conceptual
dictionary in the INGS system that we have beendeveloping. These research results open the possibility
that the story units cooperatively function with the otherstory and narrative techniques found in an INGS.
However, this study is still incomplete. For instance,
there are semantic problems in the created story units,
and an evaluation investigation is a work that needs to be
carried out in the future. In the previous section, we listed
the limitations and future directions of this study.
In addition, as stated in the first part of this paper,
this study also aims to partially develop narratology. The
tendency of the recent narratology emphasizes thenarratives in the context of diverse cultures. In thiscontext, this proposed study presents a computational and111

cognitive approach that we have recently come to call“post-narratology” [57], a narrative phenomenon in
Japan, and our narrative generation study of kabuki [4,5].
ACKNOWLEDGEMENT[12]This study was supported by JSPS KAKENHI 18K18509
and JSPS KAKENHI 21K17870.
REFERENCES[13][1] T. Ogata. Toward an Integrated Approach to Narrative
Generation: Emerging Research and Opportunities. IGI
Global, Hershey (PA), 2020.
[2] T. Ogata. Internal and External Narrative Generation
Based on Post-Narratology: Emerging Research andOpportunities. IGI Global, Hershey (PA), 2020.
[3] V. Y. Propp. Morphology of the folktale (L. Scott, Trans.).
University of Texas Press, Austin (TX), 1968.
[4] T. Ogata. A Method of Naimaze of Narratives Based on
Kabuki Analyses and Propp’s Move Techniques for an
Automated Narrative Generation System. Journal of
Robotics, Networking and Artificial Life, 2019, Volume6(2), 71–78.
[5] T. Ogata. Bridging the Gap Between Narrative
Generation Systems and Narrative Contents with KabukiOriented Narratology and Watakushi Monogatari. In: T.
Ogata, J. Ono, editors. Bridging the Gap Between AI,
Cognitive Science, and Narratology with Narrative
Generation. IGI Global, Hershey (PA), 2020, pp. 126–248.
[6] P. Dawson, M. Mäkelä. The Routledge Companion to
Narrative Theory. Routledge, London (UK), in press.
[7] T. Ogata. Concepts and Aspects of an Integrated
Narrative Generation Approach Based on PostNarratology. In: P. Dawson, M. Mäkelä, editors. The
Routledge Companion to Narrative Theory. Routledge,
London (UK), 2022 (in press).
[8] T. Ogata. Post-Narratology no Shōsō: Jinkō Chinō noJidai no Narratology ni Mukete 1 [Aspects of PostNarratology: Toward the Narratology in the Age ofArtificial Intelligence 1]. Shin’yosya, Tokyo (Japan),
2021.
[9] T. Ogata, T. Akimoto, editors. Post-Narratology ThroughComputational and Cognitive Approaches. IGI Global,
Hershey (PA), 2019.
[10] A. Utsumi. Hiyu wo Seisei Suru Koto ha Kanō Ka? [IsGenerating Metaphors Possible?]. In: T. Ogata, editor.
Post-Narratology no Shōsō: Jinkō Chinō no Jidai no
Narratology ni Mukete 1 [Aspects of Post-Narratology:
Toward the Narratology in the Age of Artificial
Intelligence 1]. Shin’yosya, Tokyo (Japan), 2021, pp. 35–
52.
[11] A. Abe. Shi wo Keisanki de Jidō Seisei Shitemiru[Attempting to Generate Automatically by Computer]. In:

[14]

[15]

[16]

[17]

[18]

112

T. Ogata, editor. Post-Narratology no Shōsō: Jinkō Chinō
no Jidai no Narratology ni Mukete 1 [Aspects of PostNarratology: Toward the Narratology in the Age ofArtificial Intelligence 1]. Shin’yosya, Tokyo (Japan),
2021, pp. 71–98.
A. Abe. The Possibility of the Generation of Literary
Works by Abduction. In: T. Ogata, T. Akimoto, editors.
Post-Narratology Through Computational and Cognitive
Approaches. IGI Global, Hershey (PA), 2019, pp. 144–
163. DOI: 10.4018/978-1-5225-7979-3.ch003
K. Araki, K. Sayama. Warau Jinkō Chinō [Laughing
Artificial Intelligence]. In: T. Ogata, editor. PostNarratology no Shōsō: Jinkō Chinō no Jidai no
Narratology ni Mukete 1 [Aspects of Post-Narratology:
Toward the Narratology in the Age of Artificial
Intelligence 1]. Shin’yosya, Tokyo (Japan), 2021, pp. 53–
69.
J. Ono, T. Ogata. Monogatari Jidō Seisei Game ni Okeru
Odoroki to Monogatari: Odorki ni Motozuku Story Seiseino Tame no Gap Gihō [Surprise and Narrative in
Automatic Narrative Generation Game: Gap Techniques
for Story Generation Based on Surprise]. In: T. Ogata,
editor. Post-Narratology no Shōsō: Jinkō Chinō no Jidai
no Narratology ni Mukete 1 [Aspects of PostNarratology: Toward the Narratology in the Age ofArtificial Intelligence 1]. Shin’yosya, Tokyo (Japan),
2021, pp. 99–130.
H. Fukushima. Ninchi Teki Contents Seisei he no Shōtai:Mikaku no Tasōteki na Contents Seisei no Kenkyū Jirei
Syōkai [Introduction to Cognitive Content Generation:
Introduction of Study Cases of Multilayered Content
Generation of Sense of Taste]. In: T. Ogata, editor. PostNarratology no Shōsō: Jinkō Chinō no Jidai no
Narratology ni Mukete 1 [Aspects of Post-Narratology:
Toward the Narratology in the Age of Artificial
Intelligence 1]. Shin’yosya, Tokyo (Japan), 2021, pp.
173–196.
H. Fukushima. Producing a Mental Representation of a
Cup of Sake: A Comparison of Experimental Methods
and a Tool for Generating Cognitive Content. In: T. Ogata,
T. Akimoto, editors. Post-Narratology ThroughComputational and Cognitive Approaches. IGI Global,
Hershey (PA), 2019, pp. 430–448. DOI: 10.4018/978-15225-7979-3.ch012
Y. Kawamura. Interactice Kōkoku Eizō Seisei System no
Kaihatsu: Tenzaisuuru Seikatsu Eizō Kara Kojin no
Tameno Eizō wo Seisei Suru [Development of anInteractive Advertising Image Generation System:
Generating Image for Individuals from Interspersed Life
Images]. In: T. Ogata, editor. Post-Narratology no Shōsō:
Jinkō Chinō no Jidai no Narratology ni Mukete 1[Aspects of Post-Narratology: Toward the Narratology in
the Age of Artificial Intelligence 1]. Shin’yosya, Tokyo(Japan), 2021, pp. 131–150.
Y. Kawamura. An Attempt of the Commercial Film
Production Support System Based on the Image Rhetoric

[19]

[20]

[21]

[22]

[23]
[24]

[25]

[26]

[27]

[28]
[29]

of Commercial Film. In: T. Ogata, T. Akimoto, editors.
Post-Narratology Through Computational and Cognitive
Approaches. IGI Global, Hershey (PA), 2019, pp. 292–
317. DOI: 10.4018/978-1-5225-7979-3.ch007
A. Kanai. Eizō to Genjitsu, Sono Ika [Image and Reality:
Their Defamiliarizations]. In: T. Ogata, editor. PostNarratology no Shōsō: Jinkō Chinō no Jidai no
Narratology ni Mukete 1 [Aspects of Post-Narratology:
Toward the Narratology in the Age of Artificial
Intelligence 1]. Shin’yosya, Tokyo (Japan), 2021, pp. 15–
33.
A. Kanai. Past, Non-Story Narrative Film, and Nostalgia.
In: T. Ogata, T. Akimoto, editors. Post-Narratology
Through Computational and Cognitive Approaches. IGI
Global, Hershey (PA), 2019, pp. 272–291. DOI:
10.4018/978-1-5225-7979-3.ch006
Y. Nitta. Elegant and Efficient Communication by HaikuLike Concise Sentences. In: T. Ogata, T. Akimoto, editors.
Post-Narratology Through Computational and Cognitive
Approaches. IGI Global, Hershey (PA), 2019, pp. 449468. DOI: 10.4018/978-1-5225-7979-3.ch013
Y. Takeda. Taking Perspectives in Digital Storytelling on
Business Planning. In: T. Ogata, T. Akimoto, editors.
Post-Narratology Through Computational and Cognitive
Approaches, IGI Global, Hershey (PA), 2019, pp. 352–
374. DOI: 10.4018/978-1-5225-7979-3.ch009
D. Herman, M. Jahn. M-L. Ryan, editors. Routledge
Encyclopedia of Narrative Theory. Routledge, London(UK), 2005.
P. Hühn, J. C. Meister, J. Pier, W. Schmid, editors. The
Living Handbook of Narratology. Interdisciplinary
Center for Narratology, University of Hamburg, Hamburg(Deutschland), May, 2009. https://www.lhn.unihamburg.de/index.html
I. Mani. Computational Narratology. The Living
Handbook of Narratology. In: P. Hühn, J. C. Meister, J.
Pier, W. Schmid, editors. Interdisciplinary Center for
Narratology, University of Hamburg, Hamburg(Deutschland), September 15, 2013. https://www.lhn.unihamburg.de/node/43.html
P. Gervás. Story Generator Algorithms. The Living
Handbook of Narratology. In: P. Hühn, J. C. Meister, J.
Pier, W. Schmid, editors. Interdisciplinary Center for
Narratology, University of Hamburg, Hamburg(Deutschland), September 12, 2019. https://www.lhn.unihamburg.de/node/35.html.
B. Neitzel. Narrativity of Computer Games. The Living
Handbook of Narratology. In: P. Hühn, J. C. Meister, J.
Pier, W. Schmid, editors. Interdisciplinary Center for
Narratology, University of Hamburg, Hamburg(Deutschland), April 22, 2014. https://www.lhn.unihamburg.de/node/127.html
G. P. Lakoff. Structural Complexity in Fairy Tales. The
Study of Man, 1972, Volume 1, 128–150.
S. Klein, J. F. Aeschlimann, M. A. Appelbaum, D. F.
Balsiger, E. J. Curtis, M. Foster, S. D. Kalish, S. J. Kamin,

[30]

[31]

[32]
[33]

[34]
[35]
[36]

[37]
[38]

[39]
[40]

[41]

[42]
[43]

[44]

113

Y. D. Lee, L. A. Price, D. F. Salsieder. Modelling Proppand Levi-Strauss in a Meta-Symbolic Simulation System.
Computer Sciences Technical Report #226. University of
Wisconsin, Madison (WI), 1974.
D. Grasbon, N. Braun. A Morphological Approach toInteractive Storytelling. Proc. of CAST 2001, Living in
Mixed Realities: Conference on Artistic, Cultural andScientific Aspects of Experimental Media Spaces. pp.
337-340, Sankt Augustin (Deutschland), 2001.
N. Szilas. Requirements for Computational Models ofInteractive Narrative. Computational Models of
Narrative: Papers from the 2010 AAAI Fall Symposium,
Technical Reports FS-10-04, 62-68, 2010.
M. A. Finlayson. Learning Narrative Structure from
Annotated Folktales. PhD diss., Massachusetts Instituteof Technology, 2012.
P. Gervás. Propp’s Morphology of the Folk Tale as a
Grammar for Generation. Paper presented at 2013
Workshop on Computational Models of Narrative, 106–122. Hamburg, December 17, 2013.
N. Okada, T. Endo. Story Generation Based on Dynamics
of the Mind. Computational Intelligence, 1992, Volume8(1), 123–160.
R. Mizoguchi. Ontology Kōgaku [Ontology Enginerring].
Ohmsha, Tokyo (Japan), 2005.
K. Takeuchi. Thesaurus with Predicate-Argument
Structure to Provide Base Framework to Determine States,
Actions, and Change-of-States. In: T. Ogata, T. Akimoto,
editors. Post-Narratology Through Computational andCognitive Approaches, IGI Global, Hershey (PA), 2019,
pp. 192–212.
E. T. Mueller. Daydreaming in Humans and Machines.
Ablex, Norwood (NJ), 1990.
S. Bringsjord, D. A. Ferrucci. Artificial Intelligence andLiterary Creativity: Inside the Mind of BRUTUS, a
Storytelling Machine. Lawrence Erlbaum, Washington(WA), 2000.
M-L. Ryan. Possible Worlds, Artificial Intelligence andNarrative Theory. Indiana University Press, Bloomington(IN), 1991.
A. Aarne. The Types of the Folktale: A Classification andBibliography (FF communications, No. 184) (S. Stith,trans). Academia Scientarum Fennica, Helsinki (Finland),1961.
A. Aarne. Mukashibanashi no Hikaku Kenkyū. Iwasaki
Bijutsusha (K. Seki, trans), Tokyo (Japan), 1969. (Antti
A.: Leitfaden der Vergleichenden. Marchenforshung,1913.)
T. Ozawa. Mukashibanashi Nyūmon [Introduction to the
Folktale], Gyousei, Tokyo (Japan), 1997.
K. Seki, J. Nomura, H. Ōshima, editors. Nihon
Mukashibanashi Taisei 11: Shiryō-hen [The Complete
Collection of Japanese Folktales, Volume 11: Data].
Kadokawa Shoten, Tokyo (Japan), 1980.
J. Ono, T. Ito, T. Ogata. Mukahibanashi no Motif noProgram-ka to Motif Kōzō no Hikaku [Programs of the

[45]

[46]

[47]

[48]

[49]

[50]

[51]

[52]

[53]

[54]

[55]

[56] T. Ogata. Building Conceptual Dictionaries for an
Integrated Narrative Generation System. Journal of
Robotics, Networking and Artificial Life, 2015, Volume1(4), 270–284.
[57] T. Ogata. Narratology and Post-Narratology. In T. Ogata,
Toward an Integrated Approach to Narrative Generation:
Emerging Research and Opportunities. IGI Global,
Hershey (PA), 2019, pp. 162-314. DOI: 10.4018/978-15225-9693-6.ch003

Motives of Folktales and the Comparison Among Motif
Structures]. Proc. of the 61th Special Interest Group on
Language Sense Processing Engineering. pp. 51–62,
2019.
K. Seki. Nihon Mukashibanashi Taisei 1: Dōbutsu
Monogatari [The Complete Collection of Japanese
Folktales, vol.1: Animal Folktales]. Kadokawa Shoten,
Tokyo (Japan), 1979.
K. Seki. Nihon Mukashibanashi Taisei 2: Honkaku
Mukashibanashi 1 [The Complete Collection of Japanese
Folktales, Volume 2: Ordinary Folktales 1]. Kadokawa
Shoten, Tokyo (Japan), 1978.
K. Seki. Nihon mukashibanashi Taisei 3: Honkaku
Mukashibanashi 2 [The Complete Collection of Japanese
Folktales, Volume 3: Ordinary Folktales 2]. Kadokawa
Shoten, Tokyo (Japan), 1978.
K. Seki. Nihon Mukashibanashi Taisei 4: Honkaku
Mukashibanashi 3 [The Complete Collection of Japanese
Folktales, Volume 4: Ordinary Folktales 3]. Kadokawa
Shoten, Tokyo (Japan), 1978.
K. Seki. Nihon Mukashibanashi Taisei 5: Honkaku
Mukashibanashi 4 [The Complete Collection of Japanese
Folktales, Volume 5: Ordinary Folktales 4]. Kadokawa
Shoten, Tokyo (Japan), 1978.
K. Seki. Nihon Mukashibanashi Taisei 6: Honkaku
Mukashibanashi 5 [The Complete Collection of Japanese
Folktales, Volume 6: Ordinary Folktales 5]. Kadokawa
Shoten, Tokyo (Japan), 1978.
K. Seki. Nihon Mukashibanashi Taisei 7: Honkaku
Mukashibanashi 6 [The Complete Collection of Japanese
Folktales, Volume 7: Ordinary Folktales 6]. Kadokawa
Shoten, Tokyo (Japan), 1979.
K. Seki. Nihon Mukashibanashi Taisei 8: Shōwa 1 [TheComplete Collection of Japanese Folktales, Volume 8:
Joke and Anecdotes 1]. Kadokawa Shoten, Tokyo (Japan),
1979.
K. Seki. Nihon Mukashibanashi Taisei 9: Shōwa 2 [TheComplete Collection of Japanese Folktales, Volume 9:
Joke and Anecdotes 2]. Kadokawa Shoten, Tokyo (Japan),
1979.
K. Seki. Nihon Mukashibanashi Taisei 10: Shōwa 3 [TheComplete Collection of Japanese Folktales, Volume 10:
Joke and Anecdotes 3]. Kadokawa Shoten, Tokyo (Japan),
1980.
K. Seki. Nomura, J., & Ōshima, H. (Eds.): Nihon
Mukashibanashi Taisei 12: Kenkyū-hen [The Complete
Collection of Japanese Folktales, Volume 12:
Researches]. Kadokawa Shoten, Tokyo (Japan), 1979.

Authors’ Introduction
Dr. Takashi Ogata
Takashi Ogata received his BSS fromWaseda University in 1983, his MS
from Tsukuba University in 1992, and
his PhD from the University of Tokyo in
1995. He has gained vast industrial
experience from working at softwaredevelopment companies since 1983. He
has been an associate professor in the
Faculty of Engineering at Yamanashi
University since 1997 and is currently a professor in the
Faculty of Software and Information Science at Iwate
Prefectural University, where he has worked since 2005.
He has published ten academic books in Japanese andEnglish regarding narrative generation and postnarratology.
Dr. Jumpei Ono

Jumepi Ono received his bachelor’s
degree from the Faculty School ofSoftware and Information Science,
Iwate Prefectural University in 2010.
He received his MS and PhD from the
Graduate School of Software andInformation Science, Iwate Prefectural
University in 2014 and 2018,
respectively. He worked as an
information and communication technology instructor at
the Vocational School of Digital Arts Sendai from 2018 to2020. He is currently an assistant professor at the Facultyof Software and Information Technology, Aomori
University.

114