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Research map / Label-efficient and robust learning / Semi-supervised learning

Global Distant Supervision for Relation Extraction

AAAI 2016 · Label-efficient and robust learning › Semi-supervised learning · approach: Self-training theory · 43 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add relation label dependency consistency (LabelDep) (ablation)MLN-Base · KBP (Surdeanu et al. 2012)best F1: 0.281 -> 0.307Helped
add argument features (ArgFea) (ablation)MLN-Base + LabelDep · KBP (Surdeanu et al. 2012)best F1: 0.307 -> 0.312Helped
add neighbor instance consistency (NeighborSim) (ablation)MLN-Base + LabelDep + ArgFea · KBP (Surdeanu et al. 2012)best F1: 0.312 -> 0.322Helped
Markov logic joint inference with KB-only supervision vs Surdeanu multi-instanceSurdeanu · KBP (Surdeanu et al. 2012)best F1: 0.278 -> 0.281Helped
full MLN with all indirect supervision vs SurdeanuSurdeanu · KBP (Surdeanu et al. 2012)best F1: 0.278 -> 0.322Helped
full MLN vs base MLN on precision (ablation)MLN-Base · KBP (Surdeanu et al. 2012)precision at best F1: 0.262 -> 0.426Helped
full MLN vs base MLN on recall (ablation)MLN-Base · KBP (Surdeanu et al. 2012)recall at best F1: 0.302 -> 0.259Hurt

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