Papers with Digital Humanities
Approaches and Challenges for Resolving Different Representations of Fictional Characters for Chinese Novels (2024.lrec-main)
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| Challenge: | Existing automatic text analysis tools and models are often developed for generic, open-domain tasks, restricting in-depth literary studies. |
| Approach: | They adapt a state-of-the-art anaphora resolution model to resolve character representations in Chinese novels by making some modifications and train a widely used BERT fine-tuned model for speaker extraction as assistance. |
| Outcome: | The proposed model is modified to resolve character representations in Chinese novels and train a BERT fine-tuned model for speaker extraction as assistance. |
Practical, Efficient, and Customizable Active Learning for Named Entity Recognition in the Digital Humanities (N19-1)
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Alexander Erdmann, David Joseph Wrisley, Benjamin Allen, Christopher Brown, Sophie Cohen-Bodénès, Micha Elsner, Yukun Feng, Brian Joseph, Béatrice Joyeux-Prunel, Marie-Catherine de Marneffe
| Challenge: | Scholars in interdisciplinary fields like the Digital Humanities are increasingly interested in semantic annotation of specialized corpora. |
| Approach: | They propose an active learning solution for named entity recognition that maximizes a custom model’s improvement per additional unit of manual annotation. |
| Outcome: | The proposed model reduces required annotation by 20-60% and outperforms a competitive active learning baseline. |
CHisIEC: An Information Extraction Corpus for Ancient Chinese History (2024.lrec-main)
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| Challenge: | Historical and cultural heritage preservation is an important branch of digital humanities, where the rich tapestry of the past meets the cutting-edge tools of the digital age. |
| Approach: | They present a dataset to evaluate NER and RE tasks in ancient Chinese history . they use four distinct entity types and twelve relation types to identify them . |
| Outcome: | The "Chinese Historical Information Extraction Corpus" is a dataset from 13 dynasties spanning over 1830 years . the dataset encompasses four distinct entity types and twelve relation types . |
Latvian National Corpora Collection – Korpuss.lv (2022.lrec-1)
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Baiba Saulite, Roberts Darģis, Normunds Gruzitis, Ilze Auzina, Kristīne Levāne-Petrova, Lauma Pretkalniņa, Laura Rituma, Peteris Paikens, Arturs Znotins, Laine Strankale, Kristīne Pokratniece, Ilmārs Poikāns, Guntis Barzdins, Inguna Skadiņa, Anda Baklāne, Valdis Saulespurēns, Jānis Ziediņš
| Challenge: | Latvian National Corpora Collection (LNCC) is a multi-institutional and multi-project effort supporting the Latvian language research and language modelling. |
| Approach: | They propose to use Latvian corpora for linguistic research and language modelling. |
| Outcome: | LNCC is a multi-institutional and multi-project effort supported by the Digital Humanities and Language Technology communities in Latvia. |