=Paper=
{{Paper
|id=Vol-1983/paper_03
|storemode=property
|title=Annotation of Metadata for Dramatic Texts: the POP-ODE Initiative
|pdfUrl=https://ceur-ws.org/Vol-1983/paper_03.pdf
|volume=Vol-1983
|authors=Vincenzo Lombardo,Rossana Damiano,Antonio Pizzo,Carmi Terzulli,Eleonora Ceccaldi,Giacomo Albert,Davide Pulizzotto
|dblpUrl=https://dblp.org/rec/conf/aiia/LombardoDPTCAP17
}}
==Annotation of Metadata for Dramatic Texts: the POP-ODE Initiative==
https://ceur-ws.org/Vol-1983/paper_03.pdf
Annotation of Metadata for Dramatic Texts: the
POP-ODE Initiative
Vincenzo Lombardo1 , Rossana Damiano1 , Antonio Pizzo2 , Carmi Terzulli1 ,
Eleonora Ceccaldi1 , Giacomo Albert2 , Davide Pulizzotto3
1
CIRMA and Dipartimento di Informatica, Università di Torino, Torino, Italy
2
CIRMA and Dipartimento di Studi Umanistici, Università di Torino, Torino, Italy
3
Département de Philosophie, Université du Québec à Montréal
Abstract. This paper addresses the problem of the metadata annota-
tion for the dramatic texts. Metadata for drama describe the dramatic
qualities of a text, connecting them with the linguistic expressions. Rely-
ing on an ontological representation of the dramatic qualities, the paper
presents an annotation environment for the creation of a corpus of an-
notated texts.
1 Introduction
Drama annotation is the process of annotating the metadata of a drama. Given a
drama expressed in some medium (text, video, audio, etc.), the process of meta-
data annotation identifies what are the elements that characterize the drama
and annotates such elements in some metadata format. For example, in the
sentence “Laertes and Polonius warn Ophelia to stay away from Hamlet.”, the
word “Laertes”, which refers to a drama element, namely a character, will be
annotated as “Character”, taken from some set of metadata. Drama annotation
projects, with the sets of metadata and annotations proposed in the scientific lit-
erature, rely upon markup languages and semantic encoding. This paper presents
an initiative for the crowdsourcing annotation of metadata for dramatic texts:
the gathering of such corpus is relevant for teaching drama through schematic
charts [13], informing models of automatic storytelling [10], preserving drama
as an intangible form of cultural heritage [12]. The initiative, called POP-ODE
(POPulating Ontology Drama Encodings), relies on a web–based system, that
provides a friendly interface to the dramatic qualities of a text. The metadata
are defined through an annotation schema that descends from a formal theory
of drama, Drammar, expressed through a computational ontology.
2 Drama and annotation
A drama is a story conveyed through characters who perform live actions: for ex-
ample, theatrical plays (Shakespeare’s Hamlet), TV series (HBO’s Sopranos 4 ),
4
http://www.hbo.com/the-sopranos, visited on 21 July 2017
30
but even reality shows (CBS’s Survivor 5 ), and games (Ubisoft’s Assassin’s Creed
6
). Drama has been pivotal for storytelling across all cultures and ages [14], grow-
ing through different media and being most pervasive, from theater and cinema
to TV and videogames [4] . Along these media, a single drama can assume several
forms, fulfilling a number of its core conditions. For example, the abstraction of
the oral tale Cinderella has, e.g., Perrault’s [19] and Disney’s [1] versions. Meta-
data annotation for dramatic texts must encode the major concepts and relations
of the drama domain, which have been shared by a majority of scholars in the
drama literature. Here, we refer to the so–called dramatic qualities, that is those
elements that are necessary for the existence of a drama, which can be found
in several drama analyses, e.g. [9, 22, 7, 23]. All the initiatives on this topic have
shared similar sets of elements, namely story units, characters or agents, actions,
intentions or plans, goals, conflicts, values at stake, emotions. These elements
are annotated in connection with media chunks (e.g., text paragraphs), often
with the goal of constructing corpora of annotated narratives and the study of
the relationships between the linguistic expression of the story in the narrative
and its content.
In order to clarify the dramatic elements, we anticipate an informal annota-
tion of a scene taken from Shakespeare’s Hamlet: the so called “nunnery” scene.
In this scene, situated in the Third Act, Ophelia is sent to Hamlet by Polonius
(her father) and Claudius (Hamlet’s uncle, the king) to confirm the assump-
tion that Hamlet’s madness is caused by his rejected love. According to the two
conspirators, Ophelia should induce him to talk about his inner feelings. At the
same time, Hamlet tries to convince Ophelia that the court is corrupted and that
she should go to a nunnery. In the middle of the scene, Hamlet puts Ophelia to
a test to prove her honesty: guessing (correctly) that the two conspirators are
hidden behind the curtain, he asks the girl to reveal where her father Polonius
is. She decides to lie, by replying that he is at home. Hamlet realizes from the
answer that also Ophelia is corrupted and consequently becomes very angry,
realizing that there is no hope to redeem the court. The climax incident in the
scene consists of a question-answer pair:
– Hamlet: “Where is your father?”
– Ophelia: “At home, my Lord!”
This is a (very relevant) story unit: boundaries are decided through the de-
tection of a specific goal pursuit, distinct from the goals pursued in the previous
unit. Here Hamlet, one of the two characters in the unit, is pursuing the goal of
proving Ophelia’s honesty. Honesty is a value for Hamlet, and Ophelia’s behav-
ior is putting at stake such a value. So, he decides to pursue the goal of proving
Ophelia honesty through a plan in which he asks a question he knows the answer
of, i.e. the current location of her father Polonius (Hamlet is sure that Polonius is
in the same room, behind a curtain). and Ophelia lies, by answering with a false
5
http://www.cbs.com/shows/survivor/, visited on 21 July 2017
6
https://www.ubisoft.com/en-US/game/assassins-creed/, visited on 21 July 2017
31
location, i.e. Polonius’ home. So, we can annotate this unit with the following
metadata:
- Unit: Hamlet tests Ophelia for honesty
- Characters: Hamlet, Ophelia
- Hamlet values at stake: Honesty
- Hamlet goal: Prove Ophelia honesty
- Hamlet plan: Asking Ophelia a rhetorical question
- Hamlet plan accomplishment: FALSE
- Ophelia values at stake: father’s authority, honesty
- Ophelia goal: Respect father’s authority
- Ophelia plan: Lying about presence of Polonius in the room
- Ophelia plan accomplishment: TRUE
- Conflict: Hamlet plan VS. Ophelia plan
- Hamlet emotions: Distress, Reproach, Anger
- Ophelia emotions: Disappointment, Joy, Shame
In particular, notice that emotions arise from the accomplishment of the
characters with respect to their values, an adaptation of OCC emotional theory
[17] [10]. So, Hamlet feels Distress because his plan fails, feels Reproach because
Ophelia is putting at stake honesty (an important value for him), and Anger
as a consequence of Distress and Reproach. Ophelia, though feels Joy because
she achieved her goal to respect father’s authority (the value with maximum
priority here), she is disappointed because her hope to convince Hamlet to talk
about his feelings failed and is ashamed because she put at stake another value
of hers, namely honesty (with a lower priority here, but always present). There
also are long spanning values at stake, goals, and plans of the characters as well
as conflicts.
These elements have been taken into account by several annotation projects,
with several non-empty intersections. Project DramaBank, which has proposed
a template based language for describing the intentional content of textual nar-
ratives, is a standalone downloadable application relying on an internal, non-
standardized representation format [3]. A media-independent model of story is
provided by the OntoMedia ontology [21], exploited across different projects
(such as the Contextus Project7 ) to annotate the narrative units of different
media objects, ranging from written literature to comics and TV fiction. In the
field of cultural heritage dissemination, the StorySpace ontology supports mu-
seum curators in linking the content of artworks through stories [25], with the
ultimate goal of enabling the generation of user tailored content retrieval. Some
initiatives also rely on automatic annotation approaches, which can overcome the
difficulties of recruiting annotators, especially when minimal schemata targeted
at grasping the regularities of written and oral narratives at the discourse level
can be worked out [20]. Finally, Drammar8 is an ontology of drama, specifically
conceived to annotate dramatic media [11], that makes the knowledge about
7
http://www.contextus.net, visited on 21 July 2017
8
https://www.di.unito.it/wikidrammar, visited on 21 July 2017
32
Scene
Dramatic
Layer tree of scenes
Scene DrammarScene Scene
Timeline123 spans
hasPreconditions hasEffects
Timeline1 Timeline2 Timeline3
Timeline
Layer Unit Unit Unit Unit
hasMember hasMember
Consistent Action Action Action Action Consistent
StateSet StateSet
State StateState contains contains contains contains State StateState
Directly Directly Directly Directly
Executable Executable Executable Executable
hasPreconditions Plan Plan Plan Plan hasEffects
list of plans list of plans
hasValue hasValue
Motivational Value Value
Layer isMotivatedBy
Abstract Abstract
Agent1 Plan Plan Agent2
intends achieves achieves intends
Belief ConflictSet Belief
knows knows
Goal Goal
hasGoal inConflictWith hasGoal
Fig. 1. Layers of ontology Drammar
drama available as a vocabulary for the linked interchange of annotations and
readily usable by automatic reasoners, such as, e.g., the calculation of charac-
ters’ emotions [10]. The usage of Drammar introduces two advantages: first, it
is complete with respect to dramatic elements and non-dependent with respect
to different media, considered as a mapping object from the metadata represen-
tation; second, as we have seen above, being a formal ontological model we can
exploit the automatic reasoning capabilities for the discovery of new metadata.
However, the use of ontology editors and reasoning tools is challenging for
drama experts [24]. For the accomplishment of the annotation task, it is crucial
to provide a friendly environment with metaphors and interfaces that directly
descend from the drama scholarship, which abstracts the annotator from the
details of the ontology representation. Here we describe a pipeline and system
for the metadata annotation of dramatic texts.
3 The Drammar ontology
In order to build a formal encoding of the dramatic elements, Drammar (see [10]
and [12] for thorough descriptions) resorts to a set of theories and models that are
well established in Artificial Intelligence and Computer Science. The ratio of this
design strategy is twofold: on the one side, it relies on widespread, sound models,
with formal properties that have been investigated in depth; on the other side, it
augments the interoperability of the representation with other encodings, which
can be contributed by several disciplines, such as, e.g., interactive storytelling
and procedural animation.
The design of Drammar ontology relies on three representation layers (see
Figure 1 for a synoptic overview). The first, the closest to the drama docu-
33
ment to be annotated, is the observable timeline (middle of Figure 1), appraised
through a literary text or an audiovisual medium, a succession of the incidents
(or actions) that happen in the drama. Incidents are assembled into discrete
structures, called units. Each succession of incidents forms a sub-timeline of the
whole timeline of the drama. This level is formalized through the Situation Cal-
culus paradigm ([15]): with sub-timelines that function as operators advancing
the story world from one state to another (states aggregated in consistent state
sets, ellipses in the figure), that work as preconditions and effects of some sub-
timeline of incidents. The actions result from the deliberation process of the
characters, named agents here.
The deliberation process is represented by the motivational layer (bottom of
Figure 1), which centers upon the notion of the character’s intention in achieving
(or trying to achieve) a goal. The intention, or the commitment of the character,
is represented by a plan, which consists of the actions that are to be carried out
in order to achieve some goal; plans are organized hierarchically, with high-level
behaviors (abstract plans) formulated as lists of lower-level plans, or subplans,
until the directly executable plans, which directly contain actions. Goals orig-
inate from the values of the characters that are put at stake and need to be
restored, given the beliefs (i.e. the knowledge) of the agents. This level is for-
malized through the rational agent paradigm, or BDI (Belief, Desire, Intention)
paradigm ([2]) (which is also applied in the computational storytelling com-
munity ([16]; [18]). This is why characters are encoded as agents in Drammar
(bottom of Figure 1). The agent is characterized by goals, beliefs, values engaged,
and plans; values can be at stake or in balance; plans can be in conflict with other
plans, possibly of other agents; a conflict set aggregates all the plans, agents and
goals that determine a dramatic scene (DrammarScene), through the game of
alternate accomplishments. The plan is the major structure of the Motivational
Layer, where all the other entities participate ([5]); plan hierarchies are trees
of plans, with abstract plans that recursively dominate children subplans, until
directly executable plans with actions that are actually performed by the agents
in the drama; each plan hierarchy pertains to a single agent; several hierarchies
(pertaining to several agents) project onto the same portion of the timeline, of-
ten with goals in conflict (actually, conflicts motivate a dramatic scene). The
success/failure in achieving goals as well as in supporting own values is respon-
sible for agents’ appraisal of the drama incidents. Plans have preconditions and
effects, which are consistent sets of states (where consistent means that there no
two states in contradiction within the set); when some plan motivates a time-
line, its preconditions and effects (the consistent state sets mentioned above) are
included in the preconditions and effect of a timeline.
The dramatic layer (top of Figure 1), which is directly inspired by the lit-
erature on drama theory, accounts for the hierachical structure of the scenes:
scenes are recursively composed of daughter scenes. Scenes span timelines, that
is sequences of units. Some scenes are called DrammarScenes, meaning that they
are motivated by some conflict over the characters’ intentions, which is the char-
acterization of scenes according to the Drammar ontology.
34
The abstract ontology, expressed as a set of logical specifications of classes
and properties, is expressed through a formal language to become a digital, tex-
tual artifact that can be fed to a software program (for manipulation, querying,
comparison, etc.). In particular, Drammar is expressed through the ontology lan-
guage, which has been designed as part of the Semantic Web project and allows
conceptual models to be described in an unambiguous way, open to understand-
ing and manipulation by both human users and software programs. The concepts
and relations introduced above are encoded in the ontology Drammar, written
in the Semantic Web language known as OWL (Ontology Web Language). In
particular, Drammar is written in a specific sub-language, OWL2 RL (Rule Lan-
guage), a syntactic and semantic restriction of OWL 2 ([10]), which provides the
adequate tradeoff between expressivity and complexity with respect to the re-
quirements of the drama domain (see ([6]) for an introduction to computational
ontologies). Also, Drammar includes classes that are intended as an interface
between the drama domain concepts and the linguistic and common sense types
of knowledge that express the content of the drama when instantiated in media,
according to the paradigm of linked data ([8]).
4 The POP-ODE initiative
The POP-ODE initiative consists of several aspects: the pipeline, the web inter-
face, the visualization tool, the corpus.
4.1 The POP-ODE pipeline
POP-ODE consists of a pipeline and a number of tools for the accomplishment
of the annotation task of metadata for dramatic texts (see Figure 2). The Fig-
ure 2 shows the pipeline vertically, on the left, from top to bottom. A drama
encoding annotator (at the top, left) works through a web-based interface to fill
the tables of a data base built according to the tenets of ontology Drammar,
which encodes the elements mentioned above, namely story units, characters,
actions, intentions or plans, goals, conflicts, values at stake (emotions are cal-
culated automatically from these data). At the same time, the annotator can
select the text chunks that correspond to some annotation (from the .txt file).
The ontology axioms have already been encoded by the drama scholar (possibly
supported by the ontology engineers), through the well-known Protègè editor9 .
Exploiting these axioms (contained in a conceptual model, OWL file), the map-
per module DB2OWL converts the data base tables into an OWL file, actually
a Drammar Instantiated Ontology file (OWL DIO file). A further software mod-
ule, OWL2CHART, extracts the individuals and properties in a XML Drammar
Chart file, which is then visualized by the interactive chart module, the user
can interact with [13]. The interactive chart module, developed for visualization
purposes and as a teaching device, here supports the validation of the produced
9
http://protege.stanford.edu, visited on 21 July 2017.
35
ontology, allowing for a fast checking of the encoded axioms. On right column,
the figure shows examples from each step. The top of the column shows a thumb-
nail of the web interface (see detail below). As example for the data base, there
are two example tables, Agent and Value, connected through the Agent identifier
(Hamlet has honesty as a value). The assertion example from the DIO OWL file
concerns the agent Marcellus who intends the plan of reaching the guard post.
The example from the XML chart representation shows the attributes of the
plan above, which determine its visualization color and shape in the interactive
chart.
4.2 The POP-ODE web interface
Figure 3 shows the web interface for the annotation. The top of the figure shows
the text selector: on the left, the Hamlet text from an authoritative source
(Shakespeare’s navigators), on the right, the text chunk that pertains to the
unit selected below. The middle of the figure shows the unit annotation, that is
the actions that have been identified by the annotator in the selected segment
of the text, recognized as a bounded unit. On the left and the right of the unit
annotation are the previous and the following unit in the story timeline, with the
values that are at stake or at balance before and after the current unit. So, in this
example, the unit concerns Polonius that asks Ophelia about her feelings; it oc-
curs after Polonius blesses Laertes on his departure and before Ophelia promises
to avoid Hamlet. The bottom of the figure concerns the plans that motivate such
a unit. In particular, going from left to right, we see that, Ophelia (the agent
or character shown at the left), who has the goal of meeting Hamlet, has the
plan of convincing her father Polonius that Hamlet is reliable, and this plan is
in conflict with Polonius’ plan who wants to convince Ophelia that she is too
candid for Hamlet. As we know from the following unit, Polonius will succeed in
convincing Ophelia, and actually Ophelia’s plan fail (see “accomplished? NO”
at the far right).
4.3 The POP-ODE visualization tool
Figure 4 shows a detailed visualization of the “nunnery” scene. The timeline
of the story units (middle of figure) is the pivotal element onto which the up-
per and lower part of the interface hinge. The header on the left contains the
description of each row (from top to bottom: play, acts, scenes, timeline and
characters, represented by their initials). The upper part of the interface con-
tains the incident structure, organized as a recursive hierarchy of acts, scenes
and units that acknowledges both the tradition of theatrical writing and the
most recent theories of scriptwriting. At each level of hierarchy, an arc marks
the presence of some segment of text: the grey box situated on each arc can
be clicked to display information about the segment (the use of boxes to signal
text content is consistently repeated through all the components). Each arc is
marked by a number of segments of different colors, which are intended as visual
cues of the participation of the characters to the segment. The lower part of
36
Text
.txt
Web-based
interface
VALUE AGENT
DB id 1 id 3
annotator
.sql name honesty
name Hamlet
descr Hamlet
honesty print Hamlet,
prince
Conceptual idAge 3
DB2OWL
nt
Model
.owl mapper
Protégé
DIO
.owl
OWL2CHART
extractor
iChart
.xml
Interactive
chart
user
Fig. 2. The ODE-Pop annotation pipeline. The lower part shows examples of the
the interface contains the characters’ individual tracks. The alignment with the
storyline shows how the characters’ intentions motivate each segment of the sto-
ryline. Plans that are abandoned by characters, because something went wrong
during the execution, are represented by incomplete arcs marked by a crossed
box. For example, Ophelia abandons the intention to return the gifts to Hamlet
37
Fig. 3. The web interface of the POP-ODE annotation: top) text selection; middle)
unit annotation; bottom) intentions-goals-conflicts annotation.
at some point. Also, notice the hierarchical representation of the intentions of
the characters, with more complex intentions encompassing shorter, simpler in-
tentions that only span one unit of the timeline. This visualization shows clearly
the conflict between Ophelia and Hamlet in this scene. Notice, for example, that
her intentions span longer subsequences of the timeline, and that their begin-
ning is always followed by the beginning of Hamlets’ intentions, signaling the
fact that he is mostly reactive in this scene.
The number of plan failures spanning the same segment, moreover, signal
the high level of conflict that characterizes this part of the play. The vertical
alignment of the characters’ intentions distributed along the tracks with the story
incidents along the timeline make the audience perceive the logical sequencing
of actions, and represents the credibility of the story in terms of a consistent
list of incidents. Long–term intentions denote a structured deliberation phase:
in the visualization of the nunnery scene the intentions attributed to Ophelia are
of a higher level with respect to Hamlet’s ones, thus showing that she holds the
overarching goal in the scene (although she fails ultimately). Opposite, Hamlet
display lower hierarchies, thus showing that he is mainly reactive to a situation
designed by others. The synchronous occurring of two characters’ intentions
(such as the ones of Hamlet and Ophelia in the ”nunnery” scene) reveals the
orchestration of conflicts. In this case, two arcs of two different characters’ tracks
happen to span the same scene or incident onto the timeline; and possibly have
opposite result on accomplished, with one of the two failing (barred rectangle and
interrupted arc). This means that there is a conflict between the characters and
our visualization provides a clear image of the orchestration of conflicts and their
execution. For example, on the left, in the scene ”returning gift”, the conflict is
between the intention of Ophelia of returning Hamlet the gifts he gave her and
the intention of Hamlet of refusing the gifts, by saying that they were not his, and
38
Fig. 4. Visualization of Hamlet nunnery scene. Through the tooltip facility of the
interface we have magnified and highlighted the contents of the nodes (proportionally
with their extension in the timeline).
.
Hamlet is successful in his intention; on the right, in the scene ”where question”,
the intention of Hamlet of testing Ophelia’s honesty fails, because Ophelia lies,
with the intention of respecting her father Polonius’ authority. The succession
of intentions displayed by a character’s track represents the character’s changes
through planning and re–planning because of the conflicts with other characters,
thus stress the emotional charge of the drama. This is particular evident in
the case of Ophelia (Figure 4): as we have seen, she has the highest level of
intentions in this scene, composed of two main intentions (bottom of the figure)
separated by a gap filled by one of Hamlet’s intentions. This shows that Ophelia
has to execute some sort of re–planning, given the failure of the first (bottom
left), so to regain the lead of the scene with another overarching plan (bottom
right). Moreover, all along the scene we see that there is a large number of failed
intentions (rectangles barred with a cross); hence, the visualization reveals the
inner nature of this scene with failed attempts on both sides to achieve their
goals: on the one hand, Ophelia wants to discover the motivation for Hamlet’s
madness, on the other, Hamlet wants to send the ”fair Ophelia” to the nunnery,
but discovers that she is not honest at all.
5 The corpus of annotated drama
The pipeline above has been used to build a crowdsourced corpus of annotated
drama. Currently, there are a few ongoing projects in annotating drama from
classic repertoire, used in theatre, cinema and media programmes. Students,
about fifty per year, receive a focussed short training in formal representation
39
and predicate logic; then, they are assigned a scene (actually, a unit) from a
classical drama to be accessed through the web interface. They fill the forms
concerning units (upper part, with previous and next unit in the timeline), on
one hand, and plans, goals, agents, and values (lower part, selected through
plans), on the other. They also annotate conflicts over plans and values that are
put at stake or in balance by the incidents in the units.
Inter-annotator agreement is managed by a supervisor, who is expert in
drama studies. The intervention of the supervisor is necessary to understand
whether some annotation is a paraphrase of another and whether the two an-
notations can be reduced to one; in case this is not possible, the two versions
remain. A typical case that occur is the segmentation of a unit into incidents:
some students only find a single incident within a unit (so, the unit is reduced to
one incident); other students encode several incidents within a unit, and usually
partial overlap boundaries of incidents. The policy of the supervisor has been
to identify the minimal units, and each segmentation proposal is expressed in
terms of the basic units built artificially.
Although the task looked very challenging, students with many kinds of back-
grounds (psychologies, media studies, philosophy, media studies) could perform
the task. The tool has proven to be effective in inferring a number of classes and
relations of the ontology that are syntactically important for the coherence of the
representation but are cumbersome and error-prone for the task of a manual (or
semi-manual) annotator. For example, when an annotator states that some scene
is spanning from this to to that unit, the tool automatically creates a timeline.
We are going to make a vast and effective test of the annotation tool over several
student classes, together with questionnaires and etnographic observations, to
evaluate the functioning of the tool and to create a vast corpus for studies in the
digital humanities.
The current corpus of annotated drama documents consists of a small number
of video and textual drama documents, respectively (see table 1). Though we
have not carried a thorough evaluation of the annotation, we have employed the
annotated documents in two applicative tasks: the first is the calculation of the
emotions felt by the characters through automatic reasoning, on the basis of the
events and the intentions manually annotated [10]; the second is the realization of
printed charts of the characters’ intentions, aligned with the timeline of incidents
[13], currently employed in the didactics of drama writing at the University
of Torino. We are going to evaluate the appropriateness of Drammar on the
adequacy of description from the point of view of research on the humanities.
6 Conclusion
In this paper, we have described the POP-ODE initiative for the metadata an-
notation of dramatic texts. We have described the annotation pipeline for drama
documents and a web-based annotation tool. The tool implements a visual in-
terface for the representation of the intentional motivations of the characters
(agents) to act within the drama. The tool has proven to be very effective in
40
Medium Work Fragment
Text Hamlet (Shakespeare) whole text
Text Mother Courage (Brecht) whole text
Text L’Arialda (Testori’s Italian neorealism) whole text
Movie Apocalypse now helicopter attack scene (ride of valkyries)
Movie Taxi driver “Are you talkin’ me?” scene
Movie Matrix bullet time scene
Movie La Dolce Vita Trevi fountain scene
Movie The Clockwork Orange Flat Block Marina scene
Movie Blade Runner “I’ve seen things ...” scene
Movie The deer hunter Russian roulette scene
Movie The Godfather Sollozzo omicide scene
Movie The Snatch dog VS. rabbit scene
Movie Kill Bill - Vol. 2 “losing the other eye” scene
Musical video clip Taylor Swift’s “You belong with me’ 3-min video
Advertisement clip “Zippo” lighter commercial 30-sec video
Animation short Oktapodi 2:30-min video
Table 1. Corpus of annotated drama documents, available on request.
inferring a number of classes and relations of the ontology that are syntacti-
cally important for the coherence of the representation but are cumbersome and
error-prone for the task of a manual (or semi-manual) annotator. We are going
to make a vast and effective test of the annotation tool over several student
classes, together with questionnaires and ethnographic observations, to evaluate
the functioning of the tool and to create a vast corpus for studies in the digital
humanities.
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