Narrative Extraction from Semantic Graphs (Short Paper)

Authors Daniil Lystopadskyi , André Santos , José Paulo Leal



PDF
Thumbnail PDF

File

OASIcs.SLATE.2023.9.pdf
  • Filesize: 0.57 MB
  • 8 pages

Document Identifiers

Author Details

Daniil Lystopadskyi
  • Faculty of Sciences, University of Porto, Portugal
André Santos
  • CRACS & INESC TEC, Porto, Portugal
  • Faculty of Sciences, University of Porto, Portugal
José Paulo Leal
  • CRACS & INESC TEC, Porto, Portugal
  • Faculty of Sciences, University of Porto, Portugal

Cite AsGet BibTex

Daniil Lystopadskyi, André Santos, and José Paulo Leal. Narrative Extraction from Semantic Graphs (Short Paper). In 12th Symposium on Languages, Applications and Technologies (SLATE 2023). Open Access Series in Informatics (OASIcs), Volume 113, pp. 9:1-9:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/OASIcs.SLATE.2023.9

Abstract

This paper proposes an interactive approach for narrative extraction from semantic graphs. The proposed approach extracts events from RDF triples, maps them to their corresponding attributes, and assembles them into a chronological sequence to form narrative graphs. The approach is evaluated on the Wikidata graph and achieves promising results in terms of narrative quality and coherence. The paper also discusses several avenues for future work, including the integration of machine learning, graph embedding methods and the exploration of advanced techniques for attention-based narrative labeling and semantic role labeling. Overall, the proposed method offers a promising approach to narrative extraction from semantic graphs and has the potential to be useful in various applications, including chatbots, conversational agents, and content creation tools.

Subject Classification

ACM Subject Classification
  • Information systems → Environment-specific retrieval
  • Information systems → Information extraction
Keywords
  • Narratives
  • Narrative Extraction
  • Information Retrieval
  • Knowledge Graphs
  • Semantic Graphs
  • Resource Description Framework
  • Web Ontology

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads

References

  1. Nandini Anantharama, Simon D. Angus, and Lachlan O'Neill. Canarex: Contextually aware narrative extraction for semantically rich text-as-data applications. In Yoav Goldberg, Zornitsa Kozareva, and Yue Zhang, editors, Findings of the Association for Computational Linguistics: EMNLP 2022, Abu Dhabi, United Arab Emirates, December 7-11, 2022, pages 3551-3564. Association for Computational Linguistics, 2022. URL: https://aclanthology.org/2022.findings-emnlp.260.
  2. Inès Blin. Building narrative structures from knowledge graphs. In Paul Groth, Anisa Rula, Jodi Schneider, Ilaria Tiddi, Elena Simperl, Panos Alexopoulos, Rinke Hoekstra, Mehwish Alam, Anastasia Dimou, and Minna Tamper, editors, The Semantic Web: ESWC 2022 Satellite Events - Hersonissos, Crete, Greece, May 29 - June 2, 2022, Proceedings, volume 13384 of Lecture Notes in Computer Science, pages 234-251. Springer, 2022. URL: https://doi.org/10.1007/978-3-031-11609-4_38.
  3. Victor de Boer. Knowledge graphs for impactful data science (keynote). In Umutcan Simsek, David Chaves-Fraga, Tassilo Pellegrini, and Sahar Vahdat, editors, Proceedings of Poster and Demo Track and Workshop Track of the 18th International Conference on Semantic Systems co-located with 18th International Conference on Semantic Systems (SEMANTiCS 2022), Vienna, Austria, September 13th to 15th, 2022, volume 3235 of CEUR Workshop Proceedings. CEUR-WS.org, 2022. URL: https://ceur-ws.org/Vol-3235/keynote1.pdf.
  4. Karine Megerdoomian, Karl Branting, Charles Horowitz, Amy Marsh, Stacy Petersen, and Eric Scott. Automated narrative extraction from administrative records. In Luther Karl Branting, editor, Proceedings of the Workshop on Artificial Intelligence and the Administrative State co-located with 17th International Conference on AI and Law (ICAIL 2019), Montreal, QC, Canada, June 17, 2019, volume 2471 of CEUR Workshop Proceedings, pages 38-48. CEUR-WS.org, 2019. URL: https://ceur-ws.org/Vol-2471/paper7.pdf.
  5. Daniele Metilli. Enhancing the Computational Representation of Narrative and Its Extraction from Text. PhD thesis, University of Pisa, Italy, 2021. URL: https://etd.adm.unipi.it/theses/available/etd-10222021-095519/.
  6. Thiloshon Nagarajah, Filip Ilievski, and Jay Pujara. Understanding narratives through dimensions of analogy. CoRR, abs/2206.07167, 2022. URL: https://doi.org/10.48550/arXiv.2206.07167.
  7. Emetis Niazmand, Gezim Sejdiu, Damien Graux, and Maria-Esther Vidal. Efficient semantic summary graphs for querying large knowledge graphs. Int. J. Inf. Manag. Data Insights, 2(1):100082, 2022. URL: https://doi.org/10.1016/j.jjimei.2022.100082.
  8. Priyanka Ranade, Sanorita Dey, Anupam Joshi, and Tim Finin. Computational understanding of narratives: A survey. IEEE Access, 10:101575-101594, 2022. URL: https://doi.org/10.1109/ACCESS.2022.3205314.
  9. Vetle Ryen, Ahmet Soylu, and Dumitru Roman. Building semantic knowledge graphs from (semi-)structured data: A review. Future Internet, 14(5):129, 2022. URL: https://doi.org/10.3390/fi14050129.
  10. Brenda Santana, Ricardo Campos, Evelin Amorim, Alípio Jorge, Purificação Silvano, and Sérgio Nunes. A survey on narrative extraction from textual data. Artificial Intelligence Review, January 2023. URL: https://doi.org/10.1007/s10462-022-10338-7.
  11. Daniil Sorokin. Knowledge Graphs and Graph Neural Networks for Semantic Parsing. PhD thesis, Technical University of Darmstadt, Germany, 2021. URL: http://tuprints.ulb.tu-darmstadt.de/19187/.
  12. Zhihua Yan and Xijin Tang. Narrative graph: Telling evolving stories based on event-centric temporal knowledge graph. Journal of Systems Science and Systems Engineering, 32(2):206-221, April 2023. URL: https://doi.org/10.1007/s11518-023-5561-0.
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail