Heterogeneous Supervision for Relation Extraction: A Representation Learning Approach
Table 8: Comparison among REHession (Ori), REHession-US (US) and REHession-TD (TD) on relation extraction and relation classification
['[BOLD] Dataset & Method  [BOLD] Wiki-KBP', '[BOLD] Dataset & Method Ori', '[BOLD] Prec  [BOLD] 0.3677', '[BOLD] Rec 0.4933', '[BOLD] F1  [BOLD] 0.4208', '[BOLD] Acc  [BOLD] 0.7277']
Effectiveness of True Label Discovery. We explore the effectiveness of the proposed context-aware true label discovery component by comparing REHession to its variants REHession-TD and REHession-US, which uses Investment or Universal Schemas to resolve conflicts. We can observe that REHession significantly outperforms its variants. Since the only difference between REHession and its variants is the model employed to resolve conflicts, this gap verifies the effectiveness of the proposed context-aware true label discovery method.