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Publication Year: 2026

71 to 80 of 1,392 Results

errors_camembertav2.tab 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 Tabular Data - 13.8 KB - 10 Variables, 159 Observations - UNF:6:dX1zhbyrPPk1DreziVEOHw== Prediction errors produced by the fine-tuned CamemBERTav2 model. Used for qualitative comparison with the other transformer-based NER models.
errors_camembert.tab 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 Tabular Data - 43.3 KB - 10 Variables, 529 Observations - UNF:6:LKJL6zjeIoC7+p0mefydwg== Prediction errors produced by the fine-tuned CamemBERT model. Documents incorrectly recognised, partially recognised, missed and spurious entities for qualitative error analysis.
errors_dalembert.tab 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 Tabular Data - 16.0 KB - 10 Variables, 185 Observations - UNF:6:+TqzKZgt8g2h9mleixtmLw== Prediction errors produced by the fine-tuned D'AlemBERT model. Documents representative recognition errors analysed in the accompanying study.
errors_europeana.tab 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 Tabular Data - 14.0 KB - 10 Variables, 161 Observations - UNF:6:r0qXPIXovg15bXXLwViguQ== Prediction errors produced by the fine-tuned Europeana BERT model. Supports the qualitative evaluation and comparison of transformer-based Named Entity Recognition models.
headline_counter_table.tab 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 Tabular Data - 1.0 KB - 12 Variables, 16 Observations - UNF:6:2raSn3MgN38lZjzDY60qZA== Table of the final evaluation results obtained on the held-out test set for all transformer-based models under different Nervaluate scenarios. Provides the principal performance metrics reported in the accompanying article and supporting the quantitative comparison of transformer...
headline_cv_summary.tab 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 Tabular Data - 206 B - 3 Variables, 4 Observations - UNF:6:LwsPP4NHhKrvsotyYYTR+w== Summary table of the cross-validation results for all transformer models, facilitating comparison of their overall performance during model selection.
headline_test_summary.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 - 291 B - MD5: a6b7319263f4f7606f6483082613f61f Summary of the final evaluation results obtained on the held-out test set for all transformer-based models averaged across three different seeds.
hp_search.tab 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 Tabular Data - 4.4 KB - 6 Variables, 72 Observations - UNF:6:zu0B79FNEke0HpLSL1WIKw== Results of the hyperparameter optimisation experiments performed for the transformer-based Named Entity Recognition models. Records the tested hyperparameter combinations and their corresponding evaluation scores used to identify the optimal training configuration.
learning_curve.tab 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 Tabular Data - 186 B - 4 Variables, 4 Observations - UNF:6:fXKPhq8vFAp9d+v7Jlmpsg== Performance metrics recorded during model training across successive epochs. Used to analyse convergence behaviour, model learning dynamics and training stability.
length_stratified.tab 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 Tabular Data - 994 B - 5 Variables, 16 Observations - UNF:6:/TrpFwgbWWGaD2ZI1dFDKQ== Evaluation results stratified by document length. Used to assess the influence of letter length on Named Entity Recognition performance across the transformer-based models.

errors_camembertav2.tab

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

Tabular Data - 13.8 KB - 10 Variables, 159 Observations -

Prediction errors produced by the fine-tuned CamemBERTav2 model. Used for qualitative comparison with the other transformer-based NER models.

errors_camembert.tab

Tabular Data - 43.3 KB - 10 Variables, 529 Observations -

Prediction errors produced by the fine-tuned CamemBERT model. Documents incorrectly recognised, partially recognised, missed and spurious entities for qualitative error analysis.

errors_dalembert.tab

Tabular Data - 16.0 KB - 10 Variables, 185 Observations -

Prediction errors produced by the fine-tuned D'AlemBERT model. Documents representative recognition errors analysed in the accompanying study.

errors_europeana.tab

Tabular Data - 14.0 KB - 10 Variables, 161 Observations -

Prediction errors produced by the fine-tuned Europeana BERT model. Supports the qualitative evaluation and comparison of transformer-based Named Entity Recognition models.

headline_counter_table.tab

Tabular Data - 1.0 KB - 12 Variables, 16 Observations -

Table of the final evaluation results obtained on the held-out test set for all transformer-based models under different Nervaluate scenarios. Provides the principal performance metrics reported in the accompanying article and supporting the quantitative comparison of transformer...

headline_cv_summary.tab

Tabular Data - 206 B - 3 Variables, 4 Observations -

Summary table of the cross-validation results for all transformer models, facilitating comparison of their overall performance during model selection.

headline_test_summary.csv

Comma Separated Values - 291 B -

Summary of the final evaluation results obtained on the held-out test set for all transformer-based models averaged across three different seeds.

hp_search.tab

Tabular Data - 4.4 KB - 6 Variables, 72 Observations -

Results of the hyperparameter optimisation experiments performed for the transformer-based Named Entity Recognition models. Records the tested hyperparameter combinations and their corresponding evaluation scores used to identify the optimal training configuration.

learning_curve.tab

Tabular Data - 186 B - 4 Variables, 4 Observations -

Performance metrics recorded during model training across successive epochs. Used to analyse convergence behaviour, model learning dynamics and training stability.

length_stratified.tab

Tabular Data - 994 B - 5 Variables, 16 Observations -

Evaluation results stratified by document length. Used to assess the influence of letter length on Named Entity Recognition performance across the transformer-based models.

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