A German Corpus for Fine-Grained Named Entity Recognition and Relation Extraction of Traffic and Industry Events
Table 7: Performance of a dependency pattern based RE model on the presented dataset.
['[BOLD] Model', '[BOLD] Precision', '[BOLD] Recall', '[BOLD] F1']
As can be expected, the performance of the RE models using gold-standard NE annotations is significantly higher than that of the models using the trained NER classifier. The dependency-based DARE model achieves an F1 score of 0.28 using gold-standard NEs, and is biased toward high-precision patterns, at the expense of recall.