--- license: eupl-1.1 task_categories: - token-classification language: - cs - de - en - fr - hu - nl - pl - sk - yi tags: - Holocaust - EHRI pretty_name: EHRI-NER size_categories: - 100K We have converted all available Extensible Markup Language (XML) files from the EHRI digital scholarly editions (i.e., EHRI Online Editions) into a trainable corpus in a format suitable for NER and have leveraged this dataset to fine-tune a multilingual language model for NER. Although the original purpose of these editions was not to provide a dataset for training NER models, we argue that they nevertheless constitute a high-quality resource that is suitable to be used in this way. ## Dataset Details The EHRI-NER dataset includes a total of 505758 tokens, with 5351 person entities, 9399 location entities, 1867 organization entities, 2237 date entities, 528 ghetto entities, and 1229 camp entities. ### Dataset Description Since 2018, the EHRI Consortium has supported the development and publication of six Holocaust-related digital scholarly editions (see [here](https://www.ehri-project.eu/ehri-online-editions)). Each edition enables digital access to facsimiles and transcripts of thematically related documents held by different EHRI partner institutions through a single web interface and unlocks new ways of presenting and browsing through historical sources using digital tools. Publishing a digital edition is a resource-intensive process. Notwithstanding the extensive archival research needed for selecting the documents, additional steps include transcribing and translating them and, most importantly, annotating words and phrases found within these texts and creating links with entities in controlled vocabularies provided by EHRI and third parties. Currently, this annotation is done manually by or under the supervision of subject matter experts, ensuring a high quality of annotations. We repurposed these resources to convert them into a dataset suitable for training NER models, which we consider as a gold standard. Each EHRI Online Edition consists of digitized documents originating from various archives that are selected, edited, and annotated by EHRI researchers using the Text Encoding Initiative (TEI) P5 standard (TEI Consortium, 2023), an XML schema, which supports their online publication. Editions enhance the edited documents by contextualizing the information contained within them and linking them to EHRI vocabularies and descriptions, and by visualizing georeferenced entities through interactive maps. Thanks to their encoding in TEI, they are fully searchable and can be filtered using facets such as spatial locations, topics, persons, organizations, and institutions. All documents within an edition have a transcript, either in their original language, a translation, or both, and have access to their facsimile. EHRI Editions are published without a regular schedule and it is possible to update them with new material or improve the already published documents. The resulting EHRI-NER dataset includes nine languages: Czech (cs), German (de), English (en), French (fr), Hungarian (hu), Dutch (nl), Polish (pl), Slovak (sk), and Yiddish (yi). - **Curated by:** EHRI - **Funded by:** European Commission call H2020-INFRAIA-2018–2020. Grant agreement ID 871111. DOI 10.3030/871111. - **Shared by:** Dermentzi, M. & Scheithauer, H. - **Language(s) (NLP):** cs, de, en, fr, hu, nl, pl, sk, yi - **License:** EUPL-1.2 ## Uses EHRI-NER is a multilingual dataset (Czech, German, English, French, Hungarian, Dutch, Polish, Slovak, Yiddish) for Named Entity Recognition (NER) in Holocaust-related texts. EHRI-NER is built by aggregating all the annotated documents in the EHRI Online Editions and converting them into a format suitable for training domain-specific NER models. ### Source Data This dataset is derived from the EHRI Online Editions, a series of six Holocaust-related digital scholarly editions (more info [here](https://www.ehri-project.eu/ehri-online-editions)). #### Who are the source data producers? This dataset was made possible thanks to the previous work of the editors and contributors of the EHRI Online Editions, including the annotators, the people who produced digital facsimiles of the original archival material, and those who created the transcripts and translations. ## Bias, Risks, and Limitations This dataset stems from a series of manually annotated digital scholarly editions, the EHRI Online Editions. The original purpose of these editions was not to provide a dataset for training NER models, although we argue that they nevertheless constitute a high-quality resource that is suitable to be used in this way. However, users should still be mindful that our dataset repurposes a resource that was not built for purpose. ### Recommendations We encourage potential users to read the paper accompanying this model before deciding to use this dataset for their purposes: Dermentzi, M., & Scheithauer, H. (2024, May 21). Repurposing Holocaust-Related Digital Scholarly Editions to Develop Multilingual Domain-Specific Named Entity Recognition Tools. Proceedings of the LREC-COLING 2024 Workshop on Holocaust Testimonies as Language Resources. HTRes@LREC-COLING 2024, Turin, Italy. ## Citation **BibTeX:** @inproceedings{dermentzi_repurposing_2024, address = {Turin, Italy}, title = {Repurposing {Holocaust}-{Related} {Digital} {Scholarly} {Editions} to {Develop} {Multilingual} {Domain}-{Specific} {Named} {Entity} {Recognition} {Tools}}, booktitle = {Proceedings of the {LREC}-{COLING} 2024 {Workshop} on {Holocaust} {Testimonies} as {Language} {Resources}}, author = {Dermentzi, Maria and Scheithauer, Hugo}, month = may, year = {2024}, pubstate={forthcoming}, } **APA:** Dermentzi, M., & Scheithauer, H. (2024, May 21). Repurposing Holocaust-Related Digital Scholarly Editions to Develop Multilingual Domain-Specific Named Entity Recognition Tools. Proceedings of the LREC-COLING 2024 Workshop on Holocaust Testimonies as Language Resources. HTRes@LREC-COLING 2024, Turin, Italy.