Improving Scholarly Knowledge Representation:Evaluating BERT-based Models for Scientific Relation Classification
Table 4: Per-relation classification results of SRC and MRC best systems on SciERC.
['Relationship Type SciERC', '[BOLD] SRC P', '[BOLD] SRC R', '[BOLD] SRC F1', '[BOLD] MRC P', '[BOLD] MRC R', '[BOLD] MRC F1']
Feature-Of and Part-Of. Since these two relations are not the most underrepresented in the corpus, we theorize that their low classification performance is owed to the natural language text diversity from which they are deduced. In this case, obtaining more annotated instances is one way to boost classifier performance. In terms of the ranked order of performances on the relations, SRC and MRC perform identically on SciERC data.