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Publication Year: 2026

11 to 20 of 1,336 Results

combined_eval_scores3.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 - 1.4 KB - 13 Variables, 24 Observations - UNF:6:IHdDRnEBZ4B81/KMQBqVKA== Consolidated spreadsheet containing the evaluation scores of all experiments performed in this study. Facilitates comparison between off-the-shelf spaCy models, the custom-trained spaCy model, and the transformer-based models across different evaluation scenarios and entity types...
cv_results.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 - 1.8 KB - 6 Variables, 20 Observations - UNF:6:72/ohGHOKcR5yXwDUXrubA== Cross-validation results for the transformer-based NER models. Reports evaluation metrics across five training runs with the best hyperparameters per model to assess model robustness.
development_set-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 - 167.4 KB - MD5: e2f0fbe2ba2975b0de463eb734e611ab Development (validation) partition of the corpus used for hyperparameter optimisation, model selection and intermediate evaluation during NER model training.
development_set-2.pkl 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 Unknown - 8.2 MB - MD5: 8d104a218fd93d5b17d6bf1671104d10 Python Pickle version of the development dataset used in the training workflows.
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.

combined_eval_scores3.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 - 1.4 KB - 13 Variables, 24 Observations -

Consolidated spreadsheet containing the evaluation scores of all experiments performed in this study. Facilitates comparison between off-the-shelf spaCy models, the custom-trained spaCy model, and the transformer-based models across different evaluation scenarios and entity types...

cv_results.tab

Tabular Data - 1.8 KB - 6 Variables, 20 Observations -

Cross-validation results for the transformer-based NER models. Reports evaluation metrics across five training runs with the best hyperparameters per model to assess model robustness.

development_set-2.csv

Comma Separated Values - 167.4 KB -

Development (validation) partition of the corpus used for hyperparameter optimisation, model selection and intermediate evaluation during NER model training.

development_set-2.pkl

Unknown - 8.2 MB -

Python Pickle version of the development dataset used in the training workflows.

errors_camembertav2.tab

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.

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