101 to 110 of 4,202 Results
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. |
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. |
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. |
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. |
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. |
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. |
Comma Separated Values - 157.2 KB -
MD5: 5f684b97b3c570eb8ada7751bdb6a075
Model predictions generated by the off-the-shelf fr_core_news_sm model using the isolated NER component (Workflow 1). Contains predicted entities, spans, labels and corresponding gold-standard annotations for the held-out test set. |
Comma Separated Values - 434 B -
MD5: 0b166ca4796478707cf53976e9ed3da1
Overall evaluation results for the complete fr_core_news_lg NLP pipeline. Reports precision, recall and F1 scores under the Strict, Exact, Partial and Type evaluation scenarios using the Nervaluate framework. |
Comma Separated Values - 1.0 KB -
MD5: 02002572ce6487ca896a367b54f4d998
Evaluation metrics for each entity type recognised by the complete fr_core_news_lg pipeline (PER, LOC and ORG). Enables comparison with the isolated NER workflow and the custom-trained model. |
Comma Separated Values - 1.9 MB -
MD5: 66e42633a3ae8e4f7ac2aa2bec9ba813
Token-level comparison between predicted and gold-standard IOB labels for the complete fr_core_news_lg NLP pipeline. Used for qualitative error analysis and comparison with the isolated NER workflow. |
