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Welcome to SODHA, the Belgian federal data archive for social sciences and the digital humanities!

Here you can find and deposit social science and digital humanities data in reusable form. Published datasets receive a DOI, making them citable like other types of publications. SODHA promotes open data by enabling reuse of research data and by safely preserving datasets in the long term.

SODHA is the Belgian service provider in the Consortium of European Social Science Data Archives (CESSDA) and is hosted by the State Archives of Belgium. SODHA was built with the help of DEMO (UCLouvain) and Interface Demography (VUB).

You can consult the SODHA Guide here, and you can read our policies here.

Want to learn more about SODHA? Consult our brochure or our presentation on the State Archives' website.

If you have any question, you can contact us at sodha@arch.be.

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Belgian Archives for Social Sciences

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The Social Study

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Royal Museums of Fine Arts

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41 to 50 of 4,139 Results

navez_spacy_custom_trained_evalpertype-2.csv Aug 25, 2026 - Replication Data for: From nineteenth-century letters to entities: "a NER pipeline for French correspondence and its methodological lessons" - Article for Digital Humanities Benelux Journal Comma Separated Values - 2.0 KB - MD5: d770abff6f7b4ac2791c99f080b2ccc9 Detailed evaluation metrics for each entity type recognised by the custom-trained model, including both standard and domain-specific categories (PER, LOC, ORG, GRP, ART, EXH and LETT).
navez_spacy_custom_trained_mismatches.csv Aug 25, 2026 - Replication Data for: From nineteenth-century letters to entities: "a NER pipeline for French correspondence and its methodological lessons" - Article for Digital Humanities Benelux Journal Comma Separated Values - 1.6 MB - MD5: bd7431776ef54f320a6345ee2c39b5d0 Token-level comparison between predicted and gold-standard IOB labels for the custom-trained spaCy model. Used for the qualitative error analysis discussed in the article.
navez_spacy_custom_trained_results.csv Aug 25, 2026 - Replication Data for: From nineteenth-century letters to entities: "a NER pipeline for French correspondence and its methodological lessons" - Article for Digital Humanities Benelux Journal Comma Separated Values - 155.9 KB - MD5: 519958789ccf7a67f90669ce21103d90 Predictions generated by the custom-trained fr_core_news_lg model after fine-tuning on the Navez gold-standard corpus. Includes all project-specific entity types (PER, LOC, ORG, GRP, ART, EXH and LETT).
navez_spacy_off_the_shelf_ner_lg_evalall-2.csv Aug 25, 2026 - Replication Data for: From nineteenth-century letters to entities: "a NER pipeline for French correspondence and its methodological lessons" - Article for Digital Humanities Benelux Journal Comma Separated Values - 410 B - MD5: 27ce89c83902be5851a3c2a3a4c0cf30 Overall evaluation results for the off-the-shelf fr_core_news_lg model. Reports precision, recall and F1 scores under the Strict, Exact, Partial and Type evaluation scenarios using the Nervaluate framework.
navez_spacy_off_the_shelf_ner_lg_evalpertype-2.csv Aug 25, 2026 - Replication Data for: From nineteenth-century letters to entities: "a NER pipeline for French correspondence and its methodological lessons" - Article for Digital Humanities Benelux Journal Comma Separated Values - 988 B - MD5: 95c489a1ea58b92b8d94ef795bc284ce Evaluation metrics for each entity type recognised by the off-the-shelf fr_core_news_lg model (PER, LOC and ORG). Enables comparison of model performance across entity categories.
navez_spacy_off_the_shelf_ner_lg_mismatches.csv Aug 25, 2026 - Replication Data for: From nineteenth-century letters to entities: "a NER pipeline for French correspondence and its methodological lessons" - Article for Digital Humanities Benelux Journal Comma Separated Values - 2.0 MB - MD5: 19e45bf3f0974a05524450f94b2b93da Token-level comparison between predicted and gold-standard IOB labels for the off-the-shelf fr_core_news_lg model. Used for qualitative error analysis and identification of recurring recognition errors.
navez_spacy_off_the_shelf_ner_lg_results.csv Aug 25, 2026 - Replication Data for: From nineteenth-century letters to entities: "a NER pipeline for French correspondence and its methodological lessons" - Article for Digital Humanities Benelux Journal Comma Separated Values - 156.9 KB - MD5: 7c28c59d7b17430f781573f98a1a5833 Model predictions generated by the off-the-shelf fr_core_news_lg model using the isolated NER component (Workflow 1). Contains predicted entities, spans, labels and corresponding gold-standard annotations for the held-out test set.
navez_spacy_off_the_shelf_ner_sm_evalall-2.csv Aug 25, 2026 - Replication Data for: From nineteenth-century letters to entities: "a NER pipeline for French correspondence and its methodological lessons" - Article for Digital Humanities Benelux Journal Comma Separated Values - 439 B - MD5: b1e463b5396ee3ecd1eb9256b33d3ccf Overall evaluation results for the off-the-shelf fr_core_news_sm model. Reports precision, recall and F1 scores under the Strict, Exact, Partial and Type evaluation scenarios using the Nervaluate framework.
navez_spacy_off_the_shelf_ner_sm_evalpertype-2.csv Aug 25, 2026 - Replication Data for: From nineteenth-century letters to entities: "a NER pipeline for French correspondence and its methodological lessons" - Article for Digital Humanities Benelux Journal Comma Separated Values - 1.1 KB - MD5: 1c6948aab25b26cdc34d89384e66544a Evaluation metrics for each entity type recognised by the off-the-shelf fr_core_news_sm model (PER, LOC and ORG). Enables comparison of model performance across entity categories.
navez_spacy_off_the_shelf_ner_sm_mismatches.csv Aug 25, 2026 - Replication Data for: From nineteenth-century letters to entities: "a NER pipeline for French correspondence and its methodological lessons" - Article for Digital Humanities Benelux Journal Comma Separated Values - 2.2 MB - MD5: fdd354911d784ba25ace9972ad447335 Token-level comparison between predicted and gold-standard IOB labels for the off-the-shelf fr_core_news_sm model. Used for qualitative error analysis and identification of recurring recognition errors.

navez_spacy_custom_trained_evalpertype-2.csv

Aug 25, 2026 - Replication Data for: From nineteenth-century letters to entities: "a NER pipeline for French correspondence and its methodological lessons" - Article for Digital Humanities Benelux Journal

Comma Separated Values - 2.0 KB -

Detailed evaluation metrics for each entity type recognised by the custom-trained model, including both standard and domain-specific categories (PER, LOC, ORG, GRP, ART, EXH and LETT).

navez_spacy_custom_trained_mismatches.csv

Comma Separated Values - 1.6 MB -

Token-level comparison between predicted and gold-standard IOB labels for the custom-trained spaCy model. Used for the qualitative error analysis discussed in the article.

navez_spacy_custom_trained_results.csv

Comma Separated Values - 155.9 KB -

Predictions generated by the custom-trained fr_core_news_lg model after fine-tuning on the Navez gold-standard corpus. Includes all project-specific entity types (PER, LOC, ORG, GRP, ART, EXH and LETT).

navez_spacy_off_the_shelf_ner_lg_evalall-2.csv

Comma Separated Values - 410 B -

Overall evaluation results for the off-the-shelf fr_core_news_lg model. Reports precision, recall and F1 scores under the Strict, Exact, Partial and Type evaluation scenarios using the Nervaluate framework.

navez_spacy_off_the_shelf_ner_lg_evalpertype-2.csv

Comma Separated Values - 988 B -

Evaluation metrics for each entity type recognised by the off-the-shelf fr_core_news_lg model (PER, LOC and ORG). Enables comparison of model performance across entity categories.

navez_spacy_off_the_shelf_ner_lg_mismatches.csv

Comma Separated Values - 2.0 MB -

Token-level comparison between predicted and gold-standard IOB labels for the off-the-shelf fr_core_news_lg model. Used for qualitative error analysis and identification of recurring recognition errors.

navez_spacy_off_the_shelf_ner_lg_results.csv

Comma Separated Values - 156.9 KB -

Model predictions generated by the off-the-shelf fr_core_news_lg model using the isolated NER component (Workflow 1). Contains predicted entities, spans, labels and corresponding gold-standard annotations for the held-out test set.

navez_spacy_off_the_shelf_ner_sm_evalall-2.csv

Comma Separated Values - 439 B -

Overall evaluation results for the off-the-shelf fr_core_news_sm model. Reports precision, recall and F1 scores under the Strict, Exact, Partial and Type evaluation scenarios using the Nervaluate framework.

navez_spacy_off_the_shelf_ner_sm_evalpertype-2.csv

Comma Separated Values - 1.1 KB -

Evaluation metrics for each entity type recognised by the off-the-shelf fr_core_news_sm model (PER, LOC and ORG). Enables comparison of model performance across entity categories.

navez_spacy_off_the_shelf_ner_sm_mismatches.csv

Comma Separated Values - 2.2 MB -

Token-level comparison between predicted and gold-standard IOB labels for the off-the-shelf fr_core_news_sm model. Used for qualitative error analysis and identification of recurring recognition errors.

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