Table 2.

Performances (%) of the pipeline and multi-task learning models. The values presented are the means of 5 runs of each model. The microaveraged P, R, and F1s of all entity or relation types are shown.

Method	Entity recognition			Relation extraction
	P	R	F1	P	R	F1
Pipeline	85.0	83.2	84.1	69.8	62.4	65.9
HardMTLa	85.0	84.1	84.5	70.2	63.6	66.7
RegMTLb	84.5	84.5	84.5	66.7	63.6	65.1
LearnMTLc	84.5	82.8	83.6	67.2	61.5	64.2

^aHardMTL: multi-task learning model for hard parameter sharing

^bRegMTL: multi-task learning model for soft parameter sharing based on regularization

^cLearnMTL: multi-task learning model for soft parameter sharing based on task relation learning