Create datasheet

README.md

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+---
+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<n<1M
+---
+
+# Dataset Card for ehri-ner/ehri-ner-all
+
+<!-- Provide a quick summary of the dataset. -->
+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
+
+<!-- Provide a longer summary of what this dataset is. -->
+
+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
+
+<!-- ### Dataset Sources
+
+
+
+- **Repository:** https://github.com/EHRI/EHRI-NER
+- **Paper:** [More Information Needed]
+ -->
+## Uses
+
+<!-- Address questions around how the dataset is intended to be used. -->
+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 section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
+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 section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
+
+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 section is meant to convey both technical and sociotechnical 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
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+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.