Volume
OASIcs, Volume 53
7th Workshop on Computational Models of Narrative (CMN 2016)
- Part of: Series: Open Access Series in Informatics (OASIcs)
Event
CMN 2016, July 11-12, 2016, Kraków, PolandEditors
Publication Details
- published at: 2016-10-25
- Publisher: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
- ISBN: 978-3-95977-020-0
- DBLP: db/conf/cmn/cmn2016
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Document
Complete Volume
OASIcs, Volume 53, CMN'16, Complete Volume
Abstract
OASIcs, Volume 53, CMN'16, Complete Volume
Cite as
7th Workshop on Computational Models of Narrative (CMN 2016). Open Access Series in Informatics (OASIcs), Volume 53, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
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@Proceedings{miller_et_al:OASIcs.CMN.2016,
title = {{OASIcs, Volume 53, CMN'16, Complete Volume}},
booktitle = {7th Workshop on Computational Models of Narrative (CMN 2016)},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-020-0},
ISSN = {2190-6807},
year = {2016},
volume = {53},
editor = {Miller, Ben and Lieto, Antonio and Ronfard, R\'{e}mi and Ware, Stephen G. and Finlayson, Mark A.},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2016},
URN = {urn:nbn:de:0030-drops-67545},
doi = {10.4230/OASIcs.CMN.2016},
annote = {Keywords: Knowledge Representation Formalisms and Methods, Artificial Intelligence, General/Cognitive simulation, Natural Language Processing, Simulation and Modeling, Problem Solving, Control Methods, and Search, Distributed Artificial Intelligence, Psychology, Literature}
}
Document
Front Matter
Frontmatter, Table of Contents, Preface, List of Authors
Abstract
Frontmatter, Table of Contents, Preface, List of Authors
Cite as
7th Workshop on Computational Models of Narrative (CMN 2016). Open Access Series in Informatics (OASIcs), Volume 53, pp. 0:i-0:x, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
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@InProceedings{miller_et_al:OASIcs.CMN.2016.0,
author = {Miller, Ben and Lieto, Antonio and Ronfard, R\'{e}mi and Ware, Stephen G. and Finlayson, Mark A.},
title = {{Frontmatter, Table of Contents, Preface, List of Authors}},
booktitle = {7th Workshop on Computational Models of Narrative (CMN 2016)},
pages = {0:i--0:x},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-020-0},
ISSN = {2190-6807},
year = {2016},
volume = {53},
editor = {Miller, Ben and Lieto, Antonio and Ronfard, R\'{e}mi and Ware, Stephen G. and Finlayson, Mark A.},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2016.0},
URN = {urn:nbn:de:0030-drops-67015},
doi = {10.4230/OASIcs.CMN.2016.0},
annote = {Keywords: Frontmatter, Table of Contents, Preface, List of Authors}
}
Document
Invited Talk
From Narrative to Visual Narrative to Audiovisual Narrative: the Multimodal Discourse Theory Connection (Invited Talk)
Abstract
Models of narrative have been proposed from many perspectives and most of these nowadays promote further the notion that narrative is a transmedial phenomenon: i.e., stories can be told making use of distinct and multiple forms of expressions. This raises a range of theoretical and practical questions, as well as rendering the task of providing computational models of narrative both more interesting and more challenging. Central to this endeavour are issues concerned with the potential mutual conditioning of narrative forms and the media employed. Methods are required for isolating narrative properties and mechanisms that may be generalised across media, while at the same time appropriately respecting differences in medial affordances. In this discussion paper I set out a corresponding approach to characterising narrative that draws on a fine-grained formal characterisation of multimodal discourse developed on the basis of both functional and formal linguistic models of discourse, generalised to the multimodal case. After briefly setting out the theoretical principles on which the account builds, I position narrative with respect to the framework and give an example of how audiovisual narratives such as film are accounted for. It will be suggested that a common anchoring in a well specified notion of discourse as an intrinsically multimodal phenomenon offers beneficial new angles on how narratives can be modelled, as well as establishing bridges between humanistic understandings of narrative and complementary computational accounts of narratives involving communicative goal-based planning.
Cite as
John A. Bateman. From Narrative to Visual Narrative to Audiovisual Narrative: the Multimodal Discourse Theory Connection (Invited Talk). In 7th Workshop on Computational Models of Narrative (CMN 2016). Open Access Series in Informatics (OASIcs), Volume 53, pp. 1:1-1:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
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@InProceedings{bateman:OASIcs.CMN.2016.1,
author = {Bateman, John A.},
title = {{From Narrative to Visual Narrative to Audiovisual Narrative: the Multimodal Discourse Theory Connection}},
booktitle = {7th Workshop on Computational Models of Narrative (CMN 2016)},
pages = {1:1--1:11},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-020-0},
ISSN = {2190-6807},
year = {2016},
volume = {53},
editor = {Miller, Ben and Lieto, Antonio and Ronfard, R\'{e}mi and Ware, Stephen G. and Finlayson, Mark A.},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2016.1},
URN = {urn:nbn:de:0030-drops-67028},
doi = {10.4230/OASIcs.CMN.2016.1},
annote = {Keywords: Narrative, computational modelling, discourse, multimodality}
}
Document
Trailer Brain: Neural and Behavioral Analysis of Social Issue Documentary Viewing with Low-Density EEG
Abstract
The effects of social issue documentaries are diverse. In particular, monetary donations and advocacy on social media are behavioral effects with public consequences. Conversely, information-seeking about an issue is potentially done in private. We designed a combined free-viewing and rapid perceptual decision-making experiment to simulate a real scenario confronted by otherwise uninformed movie-viewers, i.e., to determine what degree of support they will lend to a film based on its trailer. For a cohort of subjects with active video-streaming (e.g., Netflix) and social media accounts (e.g., Facebook), we recorded electroencephalography (EEG) and behavioral responses to trailers of social issue documentaries. We examined EEG using reliable component analysis (RCA), finding reliability within subjects across multiple viewings and across subjects within a given viewing of the same trailer. We found this reliability both over EEG captured from whole-movie viewing, as well as over 5-second movie segments. Behavioral responses following trailer viewing were not consistent from first to second viewings. Rather, support choices both tended towards extremes of support/non-support and were made faster upon second viewing. We hypothesized a relationship between reliability behavioral metrics, finding credible evidence for it in this dataset. Finally, we found that we could suitably train a naive classifier to categorize production value and narrative voice ratings given to the viewed movies from RCA-based metrics alone. In sum, our results show that EEG components during free-viewing of social issue documentary trailers can provide a useful tool to investigate viewers' neural responses during viewing, when coupled with a post hoc behavioral decision-making paradigm. The possibility of this tool being used by producers and filmmakers is also discussed.
Cite as
Jason S. Sherwin, Corinne Brenner, and John S. Johnson. Trailer Brain: Neural and Behavioral Analysis of Social Issue Documentary Viewing with Low-Density EEG. In 7th Workshop on Computational Models of Narrative (CMN 2016). Open Access Series in Informatics (OASIcs), Volume 53, pp. 2:1-2:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
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@InProceedings{sherwin_et_al:OASIcs.CMN.2016.2,
author = {Sherwin, Jason S. and Brenner, Corinne and Johnson, John S.},
title = {{Trailer Brain: Neural and Behavioral Analysis of Social Issue Documentary Viewing with Low-Density EEG}},
booktitle = {7th Workshop on Computational Models of Narrative (CMN 2016)},
pages = {2:1--2:21},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-020-0},
ISSN = {2190-6807},
year = {2016},
volume = {53},
editor = {Miller, Ben and Lieto, Antonio and Ronfard, R\'{e}mi and Ware, Stephen G. and Finlayson, Mark A.},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2016.2},
URN = {urn:nbn:de:0030-drops-67034},
doi = {10.4230/OASIcs.CMN.2016.2},
annote = {Keywords: EEG, reliable components analysis, machine learning, documentary films}
}
Document
Animation Motion in NarrativeML
Abstract
This paper describes qualitative spatial representations relevant to cartoon motion incorporated into NarrativeML, an annotation scheme intended to capture some of the core aspects of narrative. These representations are motivated by linguistic distinctions drawn from cross-linguistic studies. Motion is modeled in terms of transitions in spatial configurations, using an expressive dynamic logic with the manner and path of motion being derived from a few basic primitives. The manner is elaborated to represent properties of motion that bear on character affect. Such representations can potentially be used to support cartoon narrative summarization and question-answering. The paper discusses annotation challenges, and the use of computer vision to help in annotation. Work is underway on annotating a cartoon corpus in terms of this scheme.
Cite as
Inderjeet Mani. Animation Motion in NarrativeML. In 7th Workshop on Computational Models of Narrative (CMN 2016). Open Access Series in Informatics (OASIcs), Volume 53, pp. 3:1-3:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
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@InProceedings{mani:OASIcs.CMN.2016.3,
author = {Mani, Inderjeet},
title = {{Animation Motion in NarrativeML}},
booktitle = {7th Workshop on Computational Models of Narrative (CMN 2016)},
pages = {3:1--3:16},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-020-0},
ISSN = {2190-6807},
year = {2016},
volume = {53},
editor = {Miller, Ben and Lieto, Antonio and Ronfard, R\'{e}mi and Ware, Stephen G. and Finlayson, Mark A.},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2016.3},
URN = {urn:nbn:de:0030-drops-67042},
doi = {10.4230/OASIcs.CMN.2016.3},
annote = {Keywords: Cinematography, Motion, Qualitative Reasoning, Narrative, NarrativeML}
}
Document
Steps Towards a Formal Ontology of Narratives Based on Narratology
Abstract
Narrative is emerging as a notion that may enable overcoming the limitations of the discovery functionality (only ranked lists of objects) offered by information systems to their users. We present preliminary results on modelling narratives by means of formal ontology, by introducing a conceptualization of narratives and a mathematical expression of it. Our conceptualization tries to capture fundamental notions of narratives as defined in narratology, such as fabula, narration and plot. A validation of the conceptualization and of its mathematical specification is ongoing, based on the Semantic Web standards and on the CIDOC CRM ISO standard ontology.
Cite as
Valentina Bartalesi, Carlo Meghini, and Daniele Metilli. Steps Towards a Formal Ontology of Narratives Based on Narratology. In 7th Workshop on Computational Models of Narrative (CMN 2016). Open Access Series in Informatics (OASIcs), Volume 53, pp. 4:1-4:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
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@InProceedings{bartalesi_et_al:OASIcs.CMN.2016.4,
author = {Bartalesi, Valentina and Meghini, Carlo and Metilli, Daniele},
title = {{Steps Towards a Formal Ontology of Narratives Based on Narratology}},
booktitle = {7th Workshop on Computational Models of Narrative (CMN 2016)},
pages = {4:1--4:10},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-020-0},
ISSN = {2190-6807},
year = {2016},
volume = {53},
editor = {Miller, Ben and Lieto, Antonio and Ronfard, R\'{e}mi and Ware, Stephen G. and Finlayson, Mark A.},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2016.4},
URN = {urn:nbn:de:0030-drops-67051},
doi = {10.4230/OASIcs.CMN.2016.4},
annote = {Keywords: Ontology, Narrative}
}
Document
Exploring “Letters from the Future” by Visualizing Narrative Structure
Abstract
The growing supply of online mental health tools, platforms and treatments results in an enormous quantity of digital narrative data to be structured, analysed and interpreted. Natural Language Processing is very suitable to automatically extract textual and structural features from narratives. Visualizing these features can help to explore patterns and shifts in text content and structure. In this study, streamgraphs are developed for different types of "Letters from the Future", an online mental health promotion instrument. The visualizations show differences between as well as within the different letter types, providing directions for future research in both the visualization of narrative structure and in the field of narrative psychology. The method presented here is not limited to "Letters from the Future", the current object of study, but can in fact be used to explore any digital or digitalized textual source, like books, speech transcripts or email conversations.
Cite as
Sytske Wiegersma, Anneke M. Sools, and Bernard P. Veldkamp. Exploring “Letters from the Future” by Visualizing Narrative Structure. In 7th Workshop on Computational Models of Narrative (CMN 2016). Open Access Series in Informatics (OASIcs), Volume 53, pp. 5:1-5:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
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@InProceedings{wiegersma_et_al:OASIcs.CMN.2016.5,
author = {Wiegersma, Sytske and Sools, Anneke M. and Veldkamp, Bernard P.},
title = {{Exploring “Letters from the Future” by Visualizing Narrative Structure}},
booktitle = {7th Workshop on Computational Models of Narrative (CMN 2016)},
pages = {5:1--5:18},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-020-0},
ISSN = {2190-6807},
year = {2016},
volume = {53},
editor = {Miller, Ben and Lieto, Antonio and Ronfard, R\'{e}mi and Ware, Stephen G. and Finlayson, Mark A.},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2016.5},
URN = {urn:nbn:de:0030-drops-67064},
doi = {10.4230/OASIcs.CMN.2016.5},
annote = {Keywords: Text visualization, NLP, Narrative structure}
}
Document
Comparing Extant Story Classifiers: Results & New Directions
Abstract
Having access to a large set of stories is a necessary first step for robust and wide-ranging computational narrative modeling; happily, language data - including stories - are increasingly available in electronic form. Unhappily, the process of automatically separating stories from other forms of written discourse is not straightforward, and has resulted in a data collection bottleneck. Therefore researchers have sought to develop reliable, robust automatic algorithms for identifying story text mixed with other non-story text. In this paper we report on the reimplementation and experimental comparison of the two approaches to this task: Gordon's unigram classifier, and Corman's semantic triplet classifier. We cross-analyze their performance on both Gordon's and Corman's corpora, and discuss similarities, differences, and gaps in the performance of these classifiers, and point the way forward to improving their approaches.
Cite as
Joshua D. Eisenberg, W. Victor H. Yarlott, and Mark A. Finlayson. Comparing Extant Story Classifiers: Results & New Directions. In 7th Workshop on Computational Models of Narrative (CMN 2016). Open Access Series in Informatics (OASIcs), Volume 53, pp. 6:1-6:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
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@InProceedings{eisenberg_et_al:OASIcs.CMN.2016.6,
author = {Eisenberg, Joshua D. and Yarlott, W. Victor H. and Finlayson, Mark A.},
title = {{Comparing Extant Story Classifiers: Results \& New Directions}},
booktitle = {7th Workshop on Computational Models of Narrative (CMN 2016)},
pages = {6:1--6:10},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-020-0},
ISSN = {2190-6807},
year = {2016},
volume = {53},
editor = {Miller, Ben and Lieto, Antonio and Ronfard, R\'{e}mi and Ware, Stephen G. and Finlayson, Mark A.},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2016.6},
URN = {urn:nbn:de:0030-drops-67079},
doi = {10.4230/OASIcs.CMN.2016.6},
annote = {Keywords: Story Detection, Machine Learning, Natural Language Processing, Perceptron Learning}
}
Document
Learning a Better Motif Index: Toward Automated Motif Extraction
Abstract
Motifs are distinctive recurring elements found in folklore, and are used by folklorists to categorize and find tales across cultures and track the genetic relationships of tales over time. Motifs have significance beyond folklore as communicative devices found in news, literature, press releases, and propaganda that concisely imply a large constellation of culturally-relevant information. Until now, folklorists have only extracted motifs from narratives manually, and the conceptual structure of motifs has not been formally laid out. In this short paper we propose that it is possible to automate the extraction of both existing and new motifs from narratives using supervised learning techniques and thereby possible to learn a computational model of how folklorists determine motifs. Automatic extraction would enable the construction of a truly comprehensive motif index, which does not yet exist, as well as the automatic detection of motifs in cultural materials, opening up a new world of narrative information for analysis by anyone interested in narrative and culture. We outline an experimental design, and report on our efforts to produce a structured form of Thompson's motif index, as well as a development annotation of motifs in a small collection of Russian folklore. We propose several initial computational, supervised approaches, and describe several possible metrics of success. We describe lessons learned and difficulties encountered so far, and outline our plan going forward.
Cite as
W. Victor H. Yarlott and Mark A. Finlayson. Learning a Better Motif Index: Toward Automated Motif Extraction. In 7th Workshop on Computational Models of Narrative (CMN 2016). Open Access Series in Informatics (OASIcs), Volume 53, pp. 7:1-7:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
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@InProceedings{yarlott_et_al:OASIcs.CMN.2016.7,
author = {Yarlott, W. Victor H. and Finlayson, Mark A.},
title = {{Learning a Better Motif Index: Toward Automated Motif Extraction}},
booktitle = {7th Workshop on Computational Models of Narrative (CMN 2016)},
pages = {7:1--7:10},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-020-0},
ISSN = {2190-6807},
year = {2016},
volume = {53},
editor = {Miller, Ben and Lieto, Antonio and Ronfard, R\'{e}mi and Ware, Stephen G. and Finlayson, Mark A.},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2016.7},
URN = {urn:nbn:de:0030-drops-67088},
doi = {10.4230/OASIcs.CMN.2016.7},
annote = {Keywords: Text analysis, automated feature extraction, folklore, narrative, Russian folktales}
}
Document
ProppML: A Complete Annotation Scheme for Proppian Morphologies
Abstract
We give a preliminary description of ProppML, an annotation scheme designed to capture all the components of a Proppian-style morphological analysis of narratives. This work represents the first fully complete annotation scheme for Proppian morphologies, going beyond previous annotation schemes such as PftML, ProppOnto, Bod et al., and our own prior work. Using ProppML we have annotated Propp's morphology on fifteen tales (18,862 words) drawn from his original corpus of Russian folktales. This is a significantly larger set of data than annotated in previous studies. This pilot corpus was constructed via double annotation by two highly trained annotators, whose annotations were then combined after discussion with a third highly trained adjudicator, resulting in gold standard data which is appropriate for training machine learning algorithms. Agreement measures calculated between both annotators show very good agreement (F_1>0.75, kappa>0.9 for functions; F_1>0.6 for moves; and F_1>0.8, kappa>0.6 for dramatis personae). This is the first robust demonstration of reliable annotation of Propp's system.
Cite as
W. Victor H. Yarlott and Mark A. Finlayson. ProppML: A Complete Annotation Scheme for Proppian Morphologies. In 7th Workshop on Computational Models of Narrative (CMN 2016). Open Access Series in Informatics (OASIcs), Volume 53, pp. 8:1-8:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
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@InProceedings{yarlott_et_al:OASIcs.CMN.2016.8,
author = {Yarlott, W. Victor H. and Finlayson, Mark A.},
title = {{ProppML: A Complete Annotation Scheme for Proppian Morphologies}},
booktitle = {7th Workshop on Computational Models of Narrative (CMN 2016)},
pages = {8:1--8:19},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-020-0},
ISSN = {2190-6807},
year = {2016},
volume = {53},
editor = {Miller, Ben and Lieto, Antonio and Ronfard, R\'{e}mi and Ware, Stephen G. and Finlayson, Mark A.},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2016.8},
URN = {urn:nbn:de:0030-drops-67094},
doi = {10.4230/OASIcs.CMN.2016.8},
annote = {Keywords: Narrative structure, Computational folkloristics, Russian folktales}
}
Document
Summarizing and Comparing Story Plans
Abstract
Branching story games have gained popularity for creating unique playing experiences by adapting story content in response to user actions. Research in interactive narrative (IN) uses automated planning to generate story plans for a given story problem. However, a story planner can generate multiple story plan solutions, all of which equally-satisfy the story problem definition but contain different story content. These differences in story content are key to understanding the story branches in a story problem's solution space, however we lack narrative-theoretic metrics to compare story plans. We address this gap by first defining a story plan summarization model to capture the important story semantics from a story plan. Secondly, we define a story plan comparison metric that compares story plans based on the summarization model. Using the Glaive narrative planner and a simple story problem, we demonstrate the usefulness of using the summarization model and distance metric to characterize the different story branches in a story problem's solution space.
Cite as
Adam Amos-Binks, David L. Roberts, and R. Michael Young. Summarizing and Comparing Story Plans. In 7th Workshop on Computational Models of Narrative (CMN 2016). Open Access Series in Informatics (OASIcs), Volume 53, pp. 9:1-9:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
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@InProceedings{amosbinks_et_al:OASIcs.CMN.2016.9,
author = {Amos-Binks, Adam and Roberts, David L. and Young, R. Michael},
title = {{Summarizing and Comparing Story Plans}},
booktitle = {7th Workshop on Computational Models of Narrative (CMN 2016)},
pages = {9:1--9:16},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-020-0},
ISSN = {2190-6807},
year = {2016},
volume = {53},
editor = {Miller, Ben and Lieto, Antonio and Ronfard, R\'{e}mi and Ware, Stephen G. and Finlayson, Mark A.},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2016.9},
URN = {urn:nbn:de:0030-drops-67100},
doi = {10.4230/OASIcs.CMN.2016.9},
annote = {Keywords: artifical intelligence, planning, narrative, comparison, story}
}
Document
Leveraging a Narrative Ontology to Query a Literary Text
Abstract
In this work we propose a model for the representation of the narrative of a literary text. The model is structured in an ontology and a lexicon constituting a knowledge base that can be queried by a system. This narrative ontology, as well as describing the actors, locations, situations found in the text, provides an explicit formal representation of the timeline of the story. We will focus on a specific case study, that of the representation of a selected portion of Homer's Odyssey, in particular of the knowledge required to answer a selection of salient queries, formulated by a literary scholar. This work is being carried out within the framework of the Semantic Web by adopting models and standards such as RDF, OWL, SPARQL, and lemon among others.
Cite as
Anas Fahad Khan, Andrea Bellandi, Giulia Benotto, Francesca Frontini, Emiliano Giovannetti, and Marianne Reboul. Leveraging a Narrative Ontology to Query a Literary Text. In 7th Workshop on Computational Models of Narrative (CMN 2016). Open Access Series in Informatics (OASIcs), Volume 53, pp. 10:1-10:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
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@InProceedings{khan_et_al:OASIcs.CMN.2016.10,
author = {Khan, Anas Fahad and Bellandi, Andrea and Benotto, Giulia and Frontini, Francesca and Giovannetti, Emiliano and Reboul, Marianne},
title = {{Leveraging a Narrative Ontology to Query a Literary Text}},
booktitle = {7th Workshop on Computational Models of Narrative (CMN 2016)},
pages = {10:1--10:10},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-020-0},
ISSN = {2190-6807},
year = {2016},
volume = {53},
editor = {Miller, Ben and Lieto, Antonio and Ronfard, R\'{e}mi and Ware, Stephen G. and Finlayson, Mark A.},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2016.10},
URN = {urn:nbn:de:0030-drops-67117},
doi = {10.4230/OASIcs.CMN.2016.10},
annote = {Keywords: Ontology, Lexicon, Computational Narratology, Time, Semantic Web}
}
Document
Annotating Musical Theatre Plots on Narrative Structure and Emotional Content
Abstract
Although theoretical models of the structure of narrative arising from systematic analysis of corpora are available for domains such as Russian folk tales, there are no such sources for the plot lines of musical theatre. The present paper reports an effort of knowledge elicitation for features that characterise the narrative structure of plot in the particular domain of musical theatre. The following aspects are covered: identification of a valid vocabulary of abstract units to use in annotating musical theatre plots, development of a procedure for annotation - including a spread-sheet format for annotators to use, and a corresponding set of instructions to guide them through the process -
selection of a corpus of musical theatre pieces that would constitute the corpus to be annotated, the annotation process itself and the results of post-processing the annotated corpus in search for insights on the narrative structure of musical theatre plots.
Cite as
Pablo Gervás, Raquel Hervás, Carlos León, and Catherine V. Gale. Annotating Musical Theatre Plots on Narrative Structure and Emotional Content. In 7th Workshop on Computational Models of Narrative (CMN 2016). Open Access Series in Informatics (OASIcs), Volume 53, pp. 11:1-11:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
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@InProceedings{gervas_et_al:OASIcs.CMN.2016.11,
author = {Gerv\'{a}s, Pablo and Herv\'{a}s, Raquel and Le\'{o}n, Carlos and Gale, Catherine V.},
title = {{Annotating Musical Theatre Plots on Narrative Structure and Emotional Content}},
booktitle = {7th Workshop on Computational Models of Narrative (CMN 2016)},
pages = {11:1--11:16},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-020-0},
ISSN = {2190-6807},
year = {2016},
volume = {53},
editor = {Miller, Ben and Lieto, Antonio and Ronfard, R\'{e}mi and Ware, Stephen G. and Finlayson, Mark A.},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2016.11},
URN = {urn:nbn:de:0030-drops-67122},
doi = {10.4230/OASIcs.CMN.2016.11},
annote = {Keywords: Narrative annotation, conceptual representation of narrative, character functions, narrative schemas, musical theatre}
}
Document
Dei Genitrix: A Generative Grammar for Traditional Litanies
Abstract
The object of the present paper is a study of two traditional litanies, Litany of the Saints and Litany of Loreto, in their most ancient attested form. We will design a narrative grammar to show how their litanic structures can be generated. We propose the notion of n-selection, a narrative rule which can't be reduced to syntax or semantics: it depends on culture. We will test the grammar on the Litany to the Divine Mercy, written by Saint Faustina Kowalska in the XXth century. Our purpose is to identify the rules of the genre which allow its reproduction in more recent versions.
Cite as
Francesco Galofaro and Magdalena Maria Kubas. Dei Genitrix: A Generative Grammar for Traditional Litanies. In 7th Workshop on Computational Models of Narrative (CMN 2016). Open Access Series in Informatics (OASIcs), Volume 53, pp. 12:1-12:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
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@InProceedings{galofaro_et_al:OASIcs.CMN.2016.12,
author = {Galofaro, Francesco and Kubas, Magdalena Maria},
title = {{Dei Genitrix: A Generative Grammar for Traditional Litanies}},
booktitle = {7th Workshop on Computational Models of Narrative (CMN 2016)},
pages = {12:1--12:8},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-020-0},
ISSN = {2190-6807},
year = {2016},
volume = {53},
editor = {Miller, Ben and Lieto, Antonio and Ronfard, R\'{e}mi and Ware, Stephen G. and Finlayson, Mark A.},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2016.12},
URN = {urn:nbn:de:0030-drops-67135},
doi = {10.4230/OASIcs.CMN.2016.12},
annote = {Keywords: Litany, generative grammar, computational narratology, digital humanities, semiotics}
}
Document
What Are Analytic Narratives?
Abstract
The recently born expression "analytic narratives" refers to studies that have appeared at the boundaries of history, political science and economics. These studies purport to explain specific historical events by combining the usual narrative way of historians with the analytic tools that economists and political scientists find in rational choice theory. Game theory is prominent among these tools. The paper explains what analytic narratives are by sampling from the eponymous book Analytic Narratives by Bates, Greif, Levi, Rosenthal and Weingast and covering one outside study by Mongin (2008). It first evaluates the explanatory performance of the new genre, using some philosophy of historical explanation, and then checks its discursive consistency, using some narratology. The paper concludes that analytic narratives can usefully complement standard narratives in historical explanation, provided they specialize in the gaps that these narratives reveal, and that they are discursively consistent, despite the tension that combining a formal model with a narration creates. Two expository modes, called alternation and local supplementation, emerge from the discussion as the most appropriate ones to resolve this tension.
Cite as
Philippe Mongin. What Are Analytic Narratives?. In 7th Workshop on Computational Models of Narrative (CMN 2016). Open Access Series in Informatics (OASIcs), Volume 53, pp. 13:1-13:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
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@InProceedings{mongin:OASIcs.CMN.2016.13,
author = {Mongin, Philippe},
title = {{What Are Analytic Narratives?}},
booktitle = {7th Workshop on Computational Models of Narrative (CMN 2016)},
pages = {13:1--13:13},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-020-0},
ISSN = {2190-6807},
year = {2016},
volume = {53},
editor = {Miller, Ben and Lieto, Antonio and Ronfard, R\'{e}mi and Ware, Stephen G. and Finlayson, Mark A.},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2016.13},
URN = {urn:nbn:de:0030-drops-67141},
doi = {10.4230/OASIcs.CMN.2016.13},
annote = {Keywords: Analytic narratives, historical explanation, text, form of discourse, narratology}
}
Document
Appraisal of Computational Model for Yorùbá Folktale Narrative
Abstract
Our effort at developing computational models for African narratives, particularly those of Yorùbá folktales, is challenged by the diversity in concepts and methodologies in the discipline. This motivated us to pause and consider the various computational models of narratives in the literature. This is with a view to finding the most appropriate or otherwise adapt a closely related one for the purpose. Thorndyke's story grammar was among the models of narrative in the literature which were appraised, found close in structure and was adapted for the modelling of Yorùbá folktales narrative. In conclusion we found that the modified version of Thorndyke's model was appropriate for modelling Yorùbá folktales narrative.
Cite as
O. Deborah Ninan, George O. Ajíbádé, and Odetunji A. Odéjobí. Appraisal of Computational Model for Yorùbá Folktale Narrative. In 7th Workshop on Computational Models of Narrative (CMN 2016). Open Access Series in Informatics (OASIcs), Volume 53, pp. 14:1-14:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
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@InProceedings{ninan_et_al:OASIcs.CMN.2016.14,
author = {Ninan, O. Deborah and Aj{\'\i}b\'{a}d\'{e}, George O. and Od\'{e}job{\'\i}, Odetunji A.},
title = {{Appraisal of Computational Model for Yor\`{u}b\'{a} Folktale Narrative}},
booktitle = {7th Workshop on Computational Models of Narrative (CMN 2016)},
pages = {14:1--14:11},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-020-0},
ISSN = {2190-6807},
year = {2016},
volume = {53},
editor = {Miller, Ben and Lieto, Antonio and Ronfard, R\'{e}mi and Ware, Stephen G. and Finlayson, Mark A.},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2016.14},
URN = {urn:nbn:de:0030-drops-67158},
doi = {10.4230/OASIcs.CMN.2016.14},
annote = {Keywords: Computational, Modelling, Grammar, Folktales, Yor\`{u}b\'{a}}
}