Cases and Stories, Dimensions and Scripts
Trevor BENCH-CAPON1 , Floris BEX2
Department of Computer Science, University of Liverpool, UK
2
Department of Information and Computing Sciences, University of Utrecht,
The Netherlands
1

Abstract.
Stories and legal cases have much in common, but there are also differences. Both can be seen as a sequence of events, but in a legal casethe facts and events are legally qualified. Moreover, the point of a story
is usually implicit, whereas the outcome of a legal case is explicitly explained. Stories have been mainly used in AI and Law to explore theevidence presented in legal cases, but here we will explore the relationship on the assumption the facts of the case have already been established, and so include legal qualification and the decision. We illustrate
our approach the well known wild animals and Popov v Hayashi cases.
Keywords. stories, case based reasoning, dimensions, factors, facts.

1. Introduction
Stories and legal cases have much in common: both can be seen as collections
or sequences of particular events, instantiations of more generic scripts [18] orcase types [3]. Furthermore, both factual stories and legal cases can be used inarguments from analogy [9]. There are also clear differences: in a legal case thefacts and events are legally qualified [10], and the point of a story is usually
implicit, whereas the decision in a legal case is explicitly stated and justified.
Perhaps the most compelling use of our stories in legal reasoning is in explanation. Stories help to make sense of the facts in a case by structuring andproviding meaning to the evidence [8], thus serving as a basis for further legal
reasoning and decision-making [10]. Furthermore, it has long been recognised thata proof trace does not provide a very satisfactory explanation, and needs to be
rewritten if it is to be appealing to lawyers and lay users or used for explanation and drafting. However, the consensus model of legal case-based reasoning
currently (e.g. [2]) sees stories and evidence as distinct from factors and decisions and requiring a different style of reasoning, which leads to the narratives
disappearing once the factors have been established, so that the explanations of
the decisions are typically in terms of deduction whereas stories would be more
appealing, comprehensible and convincing.
In this paper, we will explore further the relations between stories and legal
cases by considering how dimensions from case-based reasoning [5] can serve as
elements of scripts that can be instantiated to form legal cases. Furthermore,Table 1. Instantiations of the basic case story script
PiersonKeebleYoung
Ghen

Protagonist
Post
KeebleYoung
Ghen

Antagonist
Pierson
Hickersgill
Hitchens
Rich

ProtagonistAct
Act1
Act2
Act3
Act4

InterruptAct
Act9

AntagonistAct
Act6
Act7
Act8
Act11

Popov

Popov

Hayashi

Act5

Act10

Act12

Table 2. Instantiations of the act script
Act1
Act2
Act3
Act4

subject
Post
Keeble
Young
Ghen

verb
was hunting
was shooting
was fishingharpooned

objectfox
ducks
pilchards
whale

location
open land
his pondsea
sea

motivesportcommerce
commerce
commerce

Act5
Act6
Act7
Act8
Act9
Act10
Act11
Act12

Popov
Pierson
Hickersgill
Hitchens
Ellis
crowd
Rich
Hayashimade snowcone catch
killedscaredcaughtfound
assaulted
boughtpicked up

baseballfox
ducks
pilchard
whale
Popov
whale
baseballPacific Bell Park
open landadjoining land
sea
beach
Pacific Bell Park
Nantucket
Pacific Bell Park

gain
impulsemalicecommercegain
gain
commerce
gain

we discuss how stories and scripts about the facts of a case can be connected
to stories and scripts about the legal aspects of the case, which can in turn be
used to draw legal conclusions. Thus, we present scripts for different types ofinterconnected factual stories and legal cases, and generic rules that express how
these are connected.
We will illustrate our exploration of the relationship between stories andlegal cases using the well known wild animals cases (Pierson v. Post, Keeble
v. Hickergill, Young v. Hitchens, Ghen v. Rich) and the Popov v Hayashi case(see, e.g. [6]). The wild animals cases concern ownership cases in which plaintiffs
were chasing wild animals when their pursuit was interrupted; Popov v Hayashi
concerned disputed ownership of a baseball, and is relevant because the wild
animals cases were cited when considering whether Popov’s efforts had given him
possession of the ball.

2. Stories, cases and scripts
In the 1970s, researchers in cognitive science and artificial intelligence became interested in story structure, mainly with the aim of automating story understanding and generation. Researchers such as Rumelhart [17] developed story grammars, which express the structure of stories. Building on this early work, Schankand Abelson [18] famously argued that stories consist of goal-driven action sequences called scripts, which model the way things tend to happen in the world.
For instance, the restaurant script lists the roles (customer, waiter) and sequence

of events (ordering, eating, paying) for a typical restaurant visit. These scripts
are generic, hierarchical schemes that can be instantiated to form specific stories.
In this paper, a script consists of a number of slots and a scene that puts two or
more of the slots in sequence to form a simple story.
So what is the basic script for the wild animal cases? They all have a protagonist and an antagonist. The protagonist is performing some action, when interrupted by some other action, which may or may not have been performed by the
antagonist, so we have to consider the possibility of a separate interrupting act.
For the basic case story script, we have the five slots shown in the first row ofTable 1 and a scene [ProtagonistAct InterruptAct* AntagonistAct], where* means 0 or more. The fillers for the slots for the wild animals cases are also
shown in Table 1.
As can be seen in Table 1, a case story consists of acts, basic motivatedactions [8,9]. These acts are instantiations of a sub-script of the basic case story
script, which consists of a scene [Subject Verb a/for Object on/at/in Location
on/for Motive]. The slots for the act script are shown in the first row of Table
2, and the fillers for each separate act below that. The stories that follow fromthe instantiations of the basic case story script (Table 1) and the relevant act
sub-scripts (Table 2) are as follows.
• Post was hunting a fox on open land for sport. Pierson killed the fox onopen land on impulse.
• Keeble was shooting ducks on a pond for commerce. Hickergill scared theducks on a pond for malice.
• Young was fishing for pilchards at sea for commerce. Hitchens caught thepilchards at sea for commerce.
• Ghen harpooned a whale at sea for commerce. Ellis found the whale on abeach for gain. Rich bought the whale in Nantucket for commerce.
• Popov was catching a baseball at the ballpark for gain. A crowd assaulted
Popov at the ballpark for gain. Hayashi picked up the baseball at the ballpark for gain.
These simple narratives, which relay only brute facts [4] without reference tothe law, capture the essence of each case. If they seem a little sparse we might wish
to include further sub-scripts so that the Protagonist and Antagonist slots havename and description subslots (so that, for example, ‘Post’ become ‘Post, a local
land owner’). Similarly it may be useful to include the owner under location(so that, for example, ‘a pond’ becomes ‘Keeble’s pond’). This adds colour andinterest, but still uses only non-legal facts. Next we consider the transformation
required to turn these narratives into legal cases.

3. From Narratives to Cases
To transform our simple narratives into legal cases we have to retell the stories
using terms with legal significance, to move from the world to the law [10]. Where
shall we get these legal terms, and what are the correspondences between theworld facts and the legal facts? The current consensus on reasoning with legal
cases suggests that we move from evidence to facts, from facts to factors (i.e.
legally qualified facts), and from factors to legal conclusions (e.g. [2,10]). The firststep is outside the scope of this paper: we assume that the evidence has been
weighed, a favoured narrative chosen and the facts established. So it might appear
that factors are a prime candidate for the building blocks of our legal stories.
However, there are problems with trying to form stories from factors: a lack ofstructure and the sparsity of factors. Representing cases as collections of factors
offers a bundle of legally pertinent features of a case, but it misses the structured
narrative scenes that provide context and allow the case to be readily understood.
Moreover, relatively few of the available factors appear to be present in a given
case: for example CATO has 26 factors [3], but only between 3 and 7 of thesefactors were present in any given case, which leaves too many unfilled gaps. We
therefore turn back to the origins of factors, the notion of dimensions, introducedin Rissland and Ashley’s HYPO system, most fully described in [5].
Factors represent stereotypical fact patterns which are legally significant, inthat they favour either the plaintiff or the defendant, and which are either present
in, or absent from, a case. They emerged from dimensions in the later stagesof the HYPO project, and formed the basis of the representation in CATO [3].
Dimensions in contrast represent a range, running from an extreme pro-plaintiff
point to an extreme pro-defendant point. Since the cross-over from pro-plaintiff
to pro-defendant is not fixed, dimensions cannot be said to favour either party:
which party is favoured by a dimension in a particular case depends on where onthat dimension the case lies (and where the line is drawn). For a full discussionof the relationship between dimensions and factors see [16]. There are of course
considerable advantages, both computational and formal, in using factors. Because they are Boolean and give definite support for one side or the other, theyfacilitate formal accounts of reasoning with legal cases [14], [13], [15]. But thegrouping of legal facts and their ordering on a dimension, required to provide thestructure needed to construct a story, are lost. So in this paper we see facts asdetermining a point on a dimension, referred to by the sub-range within whichthat point falls (very often these sub-ranges will correspond to factors). In script
terms, dimensions will be slots and the sub-ranges (factors) will be fillers. This
also explains the sparseness of factors: the number of dimensions sets an upperbound on the number of factors that can be present in a case.
We can take our dimensions from the extensive literature on these cases.
Dimensions for the wild animals cases have been discussed in [7], [6] and [1]. As
the nine dimensions in [1] are most expansive, we will use them in this paper.
The first column of Table 3 indicates the different dimensions, which are fairly
self-explanatory. The points on the range for each dimension are mentioned foreach case - QuarryValue, for example, ranges from Market to None, and in all
but the Pierson case the value of the quarry was market value.
The dimensions can be used to represent the elements in the cases. Note how
the dimensions are similar to the slots in a script. What is missing here, however,is a scene that allows us to provide some structure and thus helps us to makesense of a case. Various scenes are possible, depending on the level of detail inwhich we want to present the case. Take, for example, the following script.

1. Protagonist was/had ClosenessOfPursuit of [ProtagonistAct.Object],motivated by PMotive.
2. The land/sea was LandOwnership, and ProtagonistAct.Object was a
QuarryConnection visitor.
3. ProtagonistAct.Object had QuarryValue.
4. Convention gave Convention to Protagonist.
5. [InterruptAct.Subject | Antagonist] behaviour was NatureOfAct.
6. Antagonist was DefendantRole and he acted out of DMotive.
Here, [A.B] denotes the B slot that is in the sub-script under slot A (e.g. theObject of the ProtagonistAct in line 1) and [A | B] stands for ‘A or B’, soline 5 concerns the behaviour of either the Subject of the InterruptAct or the
Antagonist in case there is no interrupting act because the antagonist act isthe one that interrupts the protagonist. [A.B] denotes the B slot that is in the
sub-script under slot A.
The above script is similar to the case vectors of [1], which express a case as
the sequence of points for all nine dimensions. The script adds some explanatory
language to this, but still mainly focuses on these individual factor points, viz.
Ghen had captured a whale, motivated by gain. The sea was unowned and thewhale was a resident visitor. The whale had commercial value. Convention gave
full possession to Ghen. Ellis’ behaviour was OK. Rich was innocent and heacted out of commerce
Note that mentioning just the factor points in a dimension makes for a very sparsestory without much meaningful structure. What is missing here is the antagonist’s act as well as any information about possible interrupting acts. To havethe corresponding story make more sense, we can update the above scene withfurther information from the basic case story and act slots (Tables 1 and 2). One
option is to replace line 5 above by the following:
Table 3. Dimensions from [1]LandOwnership

PiersonKeeble

Young

Ghen

UnownedP-Freehold

UnownedUnowned
Full
Possession

Popov
Other
Owned

Nothing

Nothing

QuarryValue
QuarryConnection

SocialPreference
In HotPursuitSocialRegular

Certain To
CaptureMarketFrequent

Certain To
CaptureMarketResident

MarketResident

NatureOfAct

Impolite

Nuisance

Impolite

ActOk

PMotive
DMotive

Sport
ImpulseSolelyResponsible

Commerce
MaliceSolelyResponsible

Commerce
Commerce
SolelyResponsible

Commerce
Commerce

Gain
Gain

Innocent

Innocent

Convention
ClosenessOfPursuit

DefendantRole

CapturedInformalRight
In HotPursuitMarketFrequent
Violently
Illegal[InterruptAct, and InterruptAct.Subject behaviour was NatureOfAct. An-tagonistAct] | [AntagonistAct, and Antagonist behaviour was NatureOfAct]
This part of a scene says that the story either contains information about theinterrupting act and its nature followed by the antagonist’s act or that, if there
is no separate interrupting act, the story mentions the antagonist’s act and its
nature. This gives us the following type of story, which provides for a more understandable and coherent account of the case.
Ghen had captured a whale, motivated by gain. The sea was unowned and thewhale was a resident visitor. The whale had commercial value. Convention gave
full possession to Ghen. Ellis found the whale on a beach for gain, and Ellis’
behaviour was OK. Rich bought the whale in Nantucket for commerce. Rich
was innocent and he acted out of commerce.
The last story above shows how dimension points can be combined with basic,
non-legal facts in a case to provide a more natural account of a case. These facts
from the basic case story and act scripts (Tables 1 and 2) also play anotherimportant role, as they provide the basis for inferring the dimension points, thatis, the legal facts (Table 3).
Several of the dimension points, such as PMotive, correspond more or lessdirectly to facts (i.e. ProtagonistAct.Motive). Where this is so, we can requirethat the vocabulary is restricted to words which can be related either directlyor through a thesaurus (e.g. Livelihood = Commerce) to the dimension points.
Other dimension points need additional, non-case specific facts. QuarryValue,
for example, can be derived from the nature of the quarry and knowledge of, forexample, the price of fish, and LandOwnership requires that the owner and thenature of the tenure of ProtagonistAct.location are known. These new facts
can be added as slots in the basic case story script (Table 1). Some dimension
points furthermore require additional knowledge of what is legal or conventional.
For example, whaling conventions are held to have the force of law, whereas thoseof baseball and hunting are somewhat weaker. Similarly NatureOfAct requires
knowledge of what is and what is not illegal: while the law does uphold whaling
conventions, breaking them is not considered illegal.
The steps from brute facts to dimension points detailed above can be captured
as separate IF Slot1=X THEN Slot2=Y rules, where Slot1 is a slot in a scriptthat is related to brute facts (Tables 1 and 2) and Slot2 is a slot that represents
a dimension (Table 3). Such rules are called qualification rules by [10], because
they provide a legal qualification of brute facts. In [1], some of these rules are
given for the example cases.
IF Verb = "was shooting" THEN ClosenessOfPursuit = In Hot Pursuit
IF Verb = "harpooned" THEN Convention = FullPossession
IF Verb = "made snowcone catch" THEN Convention = InformalRight
IF Verb = "assaulted" THEN NatureOfAct = ViolentlyIllegal.

We could expand the scene and any stories based on it with the explanationof the ascription: change line 4 in the scene on the previous page to ‘Convention gave Convention to Protagonist, because he ProtagonistAct.Verb theProtagonistAct.Object’, which instantiates in a story as, for example, Convention gave full possession to Ghen because he harpooned the whale.

4. Making a Decision
We now have the story in terms of dimension points, derivable from the factual
story with some simple rules and appropriate background knowledge, which givethe legally qualified facts. The case can be represented as a vector of dimension
points: hLO, AC, COP, QV, QLC, NOA, PM, DM, DRi. What is still missing isthe denouement - the decision based on these facts. Analysis of the cases suggeststhat the plaintiff will win if he has established possession of the quarry, which canbe done in three ways: by capturing the animal, by owning the land or by convention1 . There will be a point on each of these three dimensions at which the dimension becomes, in the words of [12], a knock-out factor. But where on the dimension this point lies is debatable. Authorities are not in agreement as to whether
bodily capture, mortal wounding, or certain capture is required to establish possession. Pierson v Post is a precedent for a narrow interpretation (attributed to
Justinian) requiring actual physical possession (the extreme pro-plaintiff positionon the ClosenessOfPursuit dimension). With respect to ownership through land,
the degree of ownership must be sufficient (is a tenancy enough, or do the animals
belong to the landlord?), and the quarry must have a sufficient connection withthe land (must the quarry be resident or is being an occasional visitor, or even being merely present, enough?). With respect to convention, Ghen establishes thatconventions will be upheld for whaling, but Livingston (unsuccessfully) argued
that the law should uphold sporting conventions also.
If none of these apply, the plaintiff needs to show that act was sufficiently
wrong and that defendant was responsible. Thus the violent illegality perpetrated
on Popov did not aid his case since Hayashi was innocent of it. Had Hayashi
been the assailant, the decision may well have differed. But whether Hickergill’smalicious nuisance would have been enough for Keeble to win was not tested,since ownership of the land was decisive: mere impoliteness is not enough. So thisrequires consideration of the NatureOfAct and DefendantRole dimensions.
Finally a judgement requires a view on how interventionist the law should be.
Young established that the law would not take a position on what constituted unfair competition where both plaintiff and defendant were acting from commercial
motives. But what of Popov v Hayashi, where the parties were motiated by gain,
or a hypothetical dispute between two fox hunters? And would the quarry requirea certain value (de minimis non curat lex )? This issue requires consideration of
the two motive and the QuarryValue dimensions.
This discussion suggests that each dimension can have, by precedent or authority, two thresholds (which may co-incide), one to make it “knock-out” for
1 These are issues. They may be established by a precedent [15], or a commentary or someother document such as the Restatement of Torts [12].

the plaintiff and one for the defendant. We may also need to establish priorities(based on precedents, legal principles, or some kind of value-based argument) between these issues to resolve potential conflicts. This approach reflects the top
layer of rules found in CABARET [19], or the logical model of IBP [12] or theframework precedents of [15]. In our cases the issues are disjunctive, which is thesimplest structure, but other logical relations are possible (as in [12]). Genuine
case-based weighing of reasons should, on this view, be reserved for cases wheresome dimensions (which are needed to resolve the issues layer) fall between thedecisive thresholds (which could be few cases or many depending on how tightly
the thresholds are drawn). In [1] the theory from which these rules can be derived is encapsulated in an Abstract Dialectical Framework [11], but we use aset of rules, annotated with precedent, authorities and values promoted, and a
descriptive text.
IF LandOwnership >= P-leasehold AND QLC >= RegularVisitor
THEN Find for Plaintiff(Keeble v Hickergill) (Commentator1) (PropertyRights)(possession through land ownership).
IF Convention = FullPossession THEN Find for Plaintiff(Ghen v Rich) (Commentator2) (LessLitigation)(possession through convention).
IF ClosenessOfPursuit = Capture THEN Find for Plaintiff(Pierson v Post) (Justinian) (LegalClarity)(possession through capture).
If Closeness of Pursuit > Chasing AND NatureOfAct >= Illegal
THEN Find for Plaintiff(Precedent6) (Commentator4) (NaturalJustice)(illegal interference)
IF ClosenessOfPursuit < Capture AND NatureOfAct < Illegal
THEN Find for Defendant(Pierson v Post) (Justinian) (LegalClarity)(no possession through capture).
IF NatureOfAct < Illegal OR DefendantRole < IgnorantOfTheLaw
THEN Find for Defendant(PrecedentX) (Commentator3) (NaturalJustice)(defendant not to blame).
IF QuarryValue >= DomesticPet AND NOT (PMotive > DMotive)
AND PMOtive >= Gain THEN Find for Defendant(Young v Hitchens) (Commentator4) (Enterprise)(fair competition).
OTHERWISE The Decision is Unclear.
The rules are in priority order. We can now provide a text template forthe decision. The applicable rule will instantiate five variables: recommendation,
precedent, authority, value and text (although in our example cases the precedents
will not be instantiated, since they are themselves the cases which led to therule applying to them). This gives: [recommendation], because [text] following[precedent,] [authority] to promote [value]. The disjunctive relation between issues

means that while a finding for the plaintiff can be based on a single rule, wheremore that one rule for the defendant applies, both should be reported.
Pierson: Find for Pierson because no possession through capture following
Justinian to promote legal clarity. Find for Pierson because Pierson not toblame following Commentator3 to promote natural justice.
Keeble: Find for Keeble because possession through land ownership following Commentator1 to promote property rights.
Young: Find for Hitchens because no possession through capture following
Justinian to promote legal clarity. Find for Hitchens because fair competition following Commentator2 to promote enterpriseGhen: Find for Ghen because possession through convention following Commentator4 to promote less litigation.
Popov: The decision is unclear
We can also use these rules to consider hypothetical versions of the story. For
example: If Hayashi had assaulted Popov, then Find for Plaintiff because of illegal
interference, following precedentX and Commentator4 to promote NaturalJustice.
In Pierson the minority opinion of Livingston rejects Justinian and adopts Barbeyrac as his authority. His rule requires only that Closeness of Pursuit > Chasing when QuarryValue > DomesticPet. Thus the minority opinion in Pierson:
Find for the Plaintiff because possession through pursuit following Barbeyrac topromote socially worthwhile activity. If desired, all possible case narratives could
be envisioned in this way.

5. Discussion and Concluding Remarks
Since CATO, factors have dominated discussions of case based reasoning: their
Boolean nature has made it possible to produce a logic of precedential reasoning[14,13,15]. This level of consideration, however, presents problems of expressiveness: degrees of presence of factors seem essential to capture certain nuances [2],and seeing cases as bundles of factors loses the structural elements required toview cases as narratives. Both these aspects can be provided using dimensions,and it is the latter we have focused on in this paper. The dimensions group factors
and supply a structure, which can be used to provide a script, an outline of anarrative, which can instantiated to particular facts to present the case narrative.
By understanding legal cases in terms of scripts, we can use simple rules toreason from a narrative in terms of brute facts to a legally qualified case description, essentially a vector of points on a set of dimensions [1]. This case description
can be used together with a second set of rules based on precedents and authorities to provide a recommendation, providing, of course, that the case is coveredby existing precedents and authorities. Variants can be explored: we can vary theoriginal facts to see how this affects the legal story and the recommendation.
The path from evidence to facts to legal cases to conclusions (and back) was
earlier explored in [10]. A novelty of this paper is the use of well-known legal
cases from AI and Law - [10] focused mostly on continental law, which is basedon rules rather than precedent cases. Furthermore, in [10] the levels of brute facts

and legal facts were clearly separated, whereas in this paper we show how certain
stories and their corresponding scripts can combine brute and legal facts.
Considering factual stories and legal cases as intertwined case narratives
greatly facilitates the human understanding of the formalised case descriptions.
Thus, this work attempts to provide a basis to technologies for explanatory CBRapplications, which can be used by lawyers as well as logicians. Using a basic setof scripts and a formal representation of case facts, different case narratives canbe constructed automatically and tailored towards the specific audience of our
CBR applications. Because the domain of particular legal cases is fairly limited(at least when compared to generic CBR), such automatic story construction lies
within what is reasonably achievable.

References
[1]

[2]

[3]
[4]
[5]
[6]
[7]
[8]
[9]
[10]
[11]
[12]
[13]
[14]
[15]
[16]
[17]
[18]
[19]

L. Al-Abdulkarim, K. Atkinson, and T. Bench-Capon. Adding Dimensions and Facts
to ADF Representation of Legal Cases. Technical Report ULCS-15-004, Department ofComputer Science, University of Liverpool, 2015.
L.. Al-Abdulkarim, K. Atkinson, and T. Bench-Capon. Factors, issues and values: revisiting reasoning with cases. In Proceedings of the 15th International Conference on AI and
Law, pages 3–12, 2015.
V. Aleven. Teaching case-based argumentation through a model and examples. PhD thesis,
University of Pittsburgh, 1997.
G.E.M Anscombe. On brute facts. Analysis, pages 69–72, 1958.
K. Ashley. Modelling Legal Argument: Reasoning with Cases and Hypotheticals. Bradford
Books/MIT Press, Cambridge, MA, 1990.
T. Bench-Capon. Representing Popov v Hayashi with dimensions and factors. Artif.
Intell. Law, 20(1):15–35, 2012.
T. Bench-Capon and E. Rissland. Back to the future: dimensions revisited. In Proceedingsof JURIX 2001, pages 41–52. IOS Press, 2001.
F. Bex. Arguments, stories and criminal evidence: A formal hybrid theory. Springer,
2011.
F. Bex, T. Bench-Capon, and B. Verheij. What makes a story plausible? the need forprecedents. In Proceedings of JURIX 2011, pages 23–32, 2011.
F. Bex and B. Verheij. Legal stories and the process of proof. AI and Law, 21(3):253–278,
2013.
G. Brewka and S. Woltran. Abstract dialectical frameworks. In KR 2010, 2010.
S. Brüninghaus and K. Ashley. Predicting outcomes of case-based legal arguments. In 9thInternational Conference on Artificial Intelligence and Law, pages 233–242, 2003.
J. Horty and T. Bench-Capon. A factor-based definition of precedential constraint. Artif.
Intell. Law, 20(2):181–214, 2012.
H. Prakken and G. Sartor. Modelling reasoning with precedents in a formal dialogue game.
Artif. Intell. Law, 6(2-4):231–287, 1998.
A. Rigoni. An improved factor based approach to precedential constraint. Artif. Intell.
Law, 23(2):133–160, 2015.
E. Rissland and K. Ashley. A note on dimensions and factors. AI and Law, 10(1-3):65–77,
2002.
D.E. Rumelhart. Notes on a schema for stories. In D.G. Bobrow and A. Collins, editors,
Representation and Understanding: Studies in Cognitive Science. Academic Press, NY.
R. Schank and R. Abelson. Scripts, Plans, Goals and Understanding, An Inquiry into
Human Knowledge Structures. Lawrence Erlbaum, Hillsdale, 1977.
D. Skalak and E. Rissland. Arguments and cases: An inevitable intertwining. Artif. Intell.
Law, 1(1):3–44, 1992.