Semantic Relations between Text Segments for Semantic Storytelling: Annotation Tool - Dataset - Evaluation

Michael Raring, Malte Ostendorff, Georg Rehm

Abstract
Semantic Storytelling describes the goal to automatically and semi-automatically generate stories based on extracted, processed, classified and annotated information from large content resources. Essential is the automated processing of text segments extracted from different content resources by identifying the relevance of a text segment to a topic and its semantic relation to other text segments. In this paper we present an approach to create an automatic classifier for semantic relations between extracted text segments from different news articles. We devise custom annotation guidelines based on various discourse structure theories and annotate a dataset of 2,501 sentence pairs extracted from 2,638 Wikinews articles. For the annotation, we developed a dedicated annotation tool. Based on the constructed dataset, we perform initial experiments with Transformer language models that are trained for the automatic classification of semantic relations. Our results with promising high accuracy scores suggest the validity and applicability of our approach for future Semantic Storytelling solutions.
Anthology ID:
2022.lrec-1.526
Volume:
Proceedings of the Thirteenth Language Resources and Evaluation Conference
Month:
June
Year:
2022
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
4923–4932
Language:
URL:
https://aclanthology.org/2022.lrec-1.526
DOI:
Bibkey:
Cite (ACL):
Michael Raring, Malte Ostendorff, and Georg Rehm. 2022. Semantic Relations between Text Segments for Semantic Storytelling: Annotation Tool - Dataset - Evaluation. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 4923–4932, Marseille, France. European Language Resources Association.
Cite (Informal):
Semantic Relations between Text Segments for Semantic Storytelling: Annotation Tool - Dataset - Evaluation (Raring et al., LREC 2022)
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PDF:
https://preview.aclanthology.org/add_acl24_videos/2022.lrec-1.526.pdf
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