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File Type: Tabular Data

11 to 20 of 307 Results

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.
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.
length_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 - 533 B - 5 Variables, 9 Observations - UNF:6:XKylVdddSgIVxmbYCdrnFg== Summary statistics describing the distribution of document subword lengths in the evaluation corpus splitsand their relationship to model performance. Used to assess the number of letters affected by preprocessing.
navez_spacy_custom_trained_evalall_no_dk-2.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 - 462 B - 1 Variables, 4 Observations - UNF:6:yq7KQEdVC0k1T86KGkSn0g== Overall evaluation of the custom-trained model restricted to the standard spaCy entity types (PER, LOC and ORG). This output enables direct comparison with the off-the-shelf spaCy models presented in the article.
nervaluate_counters_overall.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 - 14 Variables, 16 Observations - UNF:6:/3uciuaa/yLyO27c+p2Cyg== Aggregated Nervaluate statistics reporting the numbers of correct, incorrect, partial, missed and spurious entity predictions on the held-out test set under the different evaluation scenarios (Strict, Exact, Partial and Type) for all transformer-based models.
per_tag_test.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 - 12.5 KB - 14 Variables, 128 Observations - UNF:6:YzGwFRM6nYl9P3yPhkiCEg== Evaluation results for each transformer-based model and each entity type (PER, LOC, ORG, GRP, ART, EXH and LETT) on the held-out test set under the Nervaluate scenarios. It enables detailed comparison of model performance across annotation categories.
significance_tests.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 - 559 B - 6 Variables, 6 Observations - UNF:6:9YJ3w4uTtbYmfNKxJTh1UA== Results of statistical significance tests comparing the performance of the evaluated Named Entity Recognition models. Used to assess whether observed performance differences are statistically meaningful.

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 -

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.

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.

length_summary.tab

Tabular Data - 533 B - 5 Variables, 9 Observations -

Summary statistics describing the distribution of document subword lengths in the evaluation corpus splitsand their relationship to model performance. Used to assess the number of letters affected by preprocessing.

navez_spacy_custom_trained_evalall_no_dk-2.tab

Tabular Data - 462 B - 1 Variables, 4 Observations -

Overall evaluation of the custom-trained model restricted to the standard spaCy entity types (PER, LOC and ORG). This output enables direct comparison with the off-the-shelf spaCy models presented in the article.

nervaluate_counters_overall.tab

Tabular Data - 1.8 KB - 14 Variables, 16 Observations -

Aggregated Nervaluate statistics reporting the numbers of correct, incorrect, partial, missed and spurious entity predictions on the held-out test set under the different evaluation scenarios (Strict, Exact, Partial and Type) for all transformer-based models.

per_tag_test.tab

Tabular Data - 12.5 KB - 14 Variables, 128 Observations -

Evaluation results for each transformer-based model and each entity type (PER, LOC, ORG, GRP, ART, EXH and LETT) on the held-out test set under the Nervaluate scenarios. It enables detailed comparison of model performance across annotation categories.

significance_tests.tab

Tabular Data - 559 B - 6 Variables, 6 Observations -

Results of statistical significance tests comparing the performance of the evaluated Named Entity Recognition models. Used to assess whether observed performance differences are statistically meaningful.

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