Improving Scholarly Knowledge Representation:Evaluating BERT-based Models for Scientific Relation Classification
Table 2: Scientific relation classification results over three datasets (SemEval18, SciERC, & Combined), four Bert model variants (Bert cased & uncased; SciBert cased & uncased), and two classification strategies (SRC & MRC). Acc. is accuracy and F1 is the macro F1-score; Top scores are in bold; Scores in red from our surveyed systems are those that are on par with the state-of-the-art reported results [6, 26] on SemEval18 and SciERC.
['[EMPTY]', '[BOLD] SRC SemEval18', '[BOLD] SRC SemEval18', '[BOLD] SRC SciERC', '[BOLD] SRC SciERC', '[BOLD] SRC Combined', '[BOLD] SRC Combined', '[BOLD] MRC SemEval18', '[BOLD] MRC SemEval18', '[BOLD] MRC SciERC', '[BOLD] MRC SciERC', '[BOLD] MRC Combined', '[BOLD] MRC Combined', '[BOLD] Avg±Std', '[BOLD] Avg±Std']
5.2.1 RQ1: What is the impact of the eight classifiers on scientific relation classification? The eight classifiers are obtained from two classification strategies built over four Bert model variants.