Multi-Task Identification of Entities, Relations, and Coreference for Scientific Knowledge Graph Construction
Table 3: Ablation study for multitask learning on SciERC development set. Each column shows results for the target task.
['Task', 'Entity Rec.', 'Relation', 'Coref.']
S7SS1SSS0Px2 Ablations We evaluate the effect of multi-task learning in each of the three tasks defined in our dataset. We observe that performance improves with each added task in the objective. For example, Entity recognition (65.7) benefits from both coreference resolution (67.5) and relation extraction (66.8). Relation extraction (37.9) significantly benefits when multi-tasked with coreference resolution (7.1% relative improvement). Coreference resolution benefits when multi-tasked with relation extraction, with 4.9% relative improvement.