| Vol-3001 urn:nbn:de:0074-3001-9 Copyright © 2021 for the individual papers by the papers' authors. Copyright © 2021 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

# STSS 2021
Shared Task on Scene Segmentation @ KONVENS 2021

### Proceedings of the Shared Task on Scene Segmentation
co-located with the 17th Conference on Natural Language Processing (KONVENS 2021)

### Düsseldorf, Germany, September 6th, 2021.

Edited by

### Albin Zehe *
Leonard Konle *
Lea Dümpelmann ****
Evelyn Gius **
Svenja Guhr **
Andreas Hotho *
Fotis Jannidis *
Lucas Kaufmann *
Markus Krug *
Frank Puppe *
Nils Reiter ***
Annekea Schreiber **

* University of Würzburg, Würzburg, Germany
** TU Darmstadt, Darmstadt, Germany
*** University of Cologne, Cologne, Germany
**** Heidelberg University, Heidelberg, Germany

## Table of Contents

### Task Description Paper

- Shared Task on Scene Segmentation @ KONVENS 2021 1-21
  Albin Zehe, Leonard Konle, Svenja Guhr, Lea Dümpelmann, Evelyn Gius, Andreas Hotho, Fotis Jannidis, Lucas Kaufmann, Markus Krug, Frank Puppe, Nils Reiter, Annekea Schreiber

### System Description Papers

- Detecting Scenes in Fiction Using the Embedding Delta Signal 22-28
  Felix Schneider, Björn Barz, Joachim Denzler
- LTUHH@STSS: Applying Coreference to Literary Scene Segmentation 29-34
  Hans Ole Hatzel, Chris Biemann
- Scene Segmentation Using Temporal, Spatial and Entity Feature Vectors 35-41
  Florian Barth, Tillmann Dönicke
- Twin BERT Contextualized Sentence Embedding Space Learning and Gradient-Boosted Decision Tree Ensembles for Scene Segmentation in German Literature 42-48
  Sebastian Gombert
- Breaking the Narrative: Scene Segmentation through Sequential Sentence Classification 49-53
  Murathan Kurfali, Mats Wirén

2021-10-26: submitted by Albin Zehe, metadata incl. bibliographic data published under Creative Commons CC0
2021-11-08: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|