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Experimenting with Unsupervised Multilingual Event Detection in Historical Newspapers

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From Born-Physical to Born-Virtual: Augmenting Intelligence in Digital Libraries (ICADL 2022)

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Abstract

To prevent historical knowledge’s fading, research in event detection could facilitate access to digitized collections. In this paper, we propose a method for annotating multilingual historical documents for event detection in an unsupervised manner by leveraging entities and semantic notions of event types. We automatically annotate the documents by relying on dependency parse trees and automatic semantic mapping to event-based frames, with a focus on the multilingual transfer between frames and candidate events. The documents are afterward verified by native speakers, Digital Humanities researchers. We also report on experimental results of event detection in historical newspapers with a state-of-the-art model. We demonstrate that our approach allows for easy language adaptation by presenting two study cases with knowledge extracted from German newspapers from 1911 to 1933 regarding events surrounding International Women’s Day and from French newspapers between 1900 and 1944 related to the abolition of guillotine executions in France. Our preliminary findings show that this type of approach could alleviate the need for manual annotation by also providing a practical course of action toward unsupervised event detection from multilingual digitized and historical documents.

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Notes

  1. 1.

    https://www.newseye.eu/.

  2. 2.

    https://www.ldc.upenn.edu/sites/www.ldc.upenn.edu/files/english-events-guidelines-v5.4.3.pdf.

  3. 3.

    An example of the Execution frame can be viewed at Framenet2 website.

  4. 4.

    We chose movements, conflictual events, and membership in organizations.

  5. 5.

    We used spaCy 3.1+ [23] with the model xx_ent_wiki_sm https://spacy.io/models/xx.

  6. 6.

    We are aware that BERT was trained for representing true sentences rather than pseudo-sentences. However, we consider that BERT might generate an embedding that represents the context in which all the event triggers are frequently used.

  7. 7.

    As we use multilingual BERT, even when the training is English, the model should be able to predict events in other languages in a zero-shot manner.

  8. 8.

    Translation: In order to bring about this desired state, we send our greetings to our sisters all over the world and call on them to demonstrate together with us against the continuation of the war on International Women’s Day.

  9. 9.

    This threshold was chosen experimentally after we verified the dismissed articles.

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Acknowledgments

This work has been supported by the European Union’s Horizon 2020 research and innovation program under grants 770299 (NewsEye) and 825153 (Embeddia). Also, it has been supported by the ANNA (2019-1R40226) and TERMITRAD (2020–2019-8510010) projects funded by the Nouvelle-Aquitaine Region, France.

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Authors and Affiliations

  1. University of La Rochelle, L3i, F-17000, La Rochelle, France

    Emanuela Boros, Luis Adrián Cabrera-Diego & Antoine Doucet

  2. Jus Mundi, F-75008, Paris, France

    Luis Adrián Cabrera-Diego

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  1. Emanuela Boros
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Correspondence to Emanuela Boros .

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  1. National Taiwan Normal University, Taipei, Taiwan

    Yuen-Hsien Tseng

  2. Doshisha University, Kyoto, Japan

    Marie Katsurai

  3. VNU University of Engineering and Technology, Hanoi, Vietnam

    Hoa N. Nguyen

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Boros, E., Cabrera-Diego, L.A., Doucet, A. (2022). Experimenting with Unsupervised Multilingual Event Detection in Historical Newspapers. In: Tseng, YH., Katsurai, M., Nguyen, H.N. (eds) From Born-Physical to Born-Virtual: Augmenting Intelligence in Digital Libraries. ICADL 2022. Lecture Notes in Computer Science, vol 13636. Springer, Cham. https://doi.org/10.1007/978-3-031-21756-2_15

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