SRL4ORL: Improving Opinion Role Labeling using Multi-task Learning with Semantic Role Labeling

NAACL 2018 Ana MarasovićAnette Frank

For over a decade, machine learning has been used to extract opinion-holder-target structures from text to answer the question "Who expressed what kind of sentiment towards what?". Recent neural approaches do not outperform the state-of-the-art feature-based models for Opinion Role Labeling (ORL)... (read more)

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Evaluation Results from the Paper


#2 best model for Fine-Grained Opinion Analysis on MPQA (using extra training data)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK USES EXTRA
TRAINING DATA
COMPARE
Fine-Grained Opinion Analysis MPQA FS-MTL Holder Binary F1 83.80 # 2
Fine-Grained Opinion Analysis MPQA FS-MTL Target Binary F1 72.06 # 2