TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK
Semantic Role Labeling (predicted predicates)	CoNLL 2005	He et al. 2018 + ELMo	F1	86.0	# 2
Semantic Role Labeling	CoNLL 2005	He et al. (2018)	F1	82.5	# 15
Semantic Role Labeling	CoNLL 2005	He et al. (2018) + ELMo	F1	86.0	# 13
Semantic Role Labeling (predicted predicates)	CoNLL 2005	He et al. (2018)	F1	86.0	# 2
Semantic Role Labeling (predicted predicates)	CoNLL 2005	He et al. 2018	F1	82.5	# 5
Semantic Role Labeling (predicted predicates)	CoNLL 2012	He et al. 2018 + ELMo	F1	82.9	# 4
Semantic Role Labeling (predicted predicates)	CoNLL 2012	He et al. 2018	F1	79.8	# 7
Semantic Role Labeling	OntoNotes	He et al.,	F1	85.5	# 11
Semantic Role Labeling	OntoNotes	He et al.	F1	82.1	# 15

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	`[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/jointly-predicting-predicates-and-arguments/semantic-role-labeling-predicted-predicates)](https://paperswithcode.com/sota/semantic-role-labeling-predicted-predicates?p=jointly-predicting-predicates-and-arguments)`
	`[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/jointly-predicting-predicates-and-arguments/semantic-role-labeling-predicted-predicates-1)](https://paperswithcode.com/sota/semantic-role-labeling-predicted-predicates-1?p=jointly-predicting-predicates-and-arguments)`
	`[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/jointly-predicting-predicates-and-arguments/semantic-role-labeling-on-ontonotes)](https://paperswithcode.com/sota/semantic-role-labeling-on-ontonotes?p=jointly-predicting-predicates-and-arguments)`
	`[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/jointly-predicting-predicates-and-arguments/semantic-role-labeling-on-conll-2005)](https://paperswithcode.com/sota/semantic-role-labeling-on-conll-2005?p=jointly-predicting-predicates-and-arguments)`

Jointly Predicting Predicates and Arguments in Neural Semantic Role Labeling

ACL 2018 · Luheng He, Kenton Lee, Omer Levy, Luke Zettlemoyer ·

Recent BIO-tagging-based neural semantic role labeling models are very high performing, but assume gold predicates as part of the input and cannot incorporate span-level features. We propose an end-to-end approach for jointly predicting all predicates, arguments spans, and the relations between them. The model makes independent decisions about what relationship, if any, holds between every possible word-span pair, and learns contextualized span representations that provide rich, shared input features for each decision. Experiments demonstrate that this approach sets a new state of the art on PropBank SRL without gold predicates.

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Semantic Role Labeling

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OntoNotes 5.0 CoNLL CoNLL-2012

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Ranked #2 on Semantic Role Labeling (predicted predicates) on CoNLL 2005

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Task	Dataset	Model	Metric Name	Metric Value	Global Rank	Benchmark
Semantic Role Labeling (predicted predicates)	CoNLL 2005	He et al. 2018 + ELMo	F1	86.0	# 2	Compare
Semantic Role Labeling	CoNLL 2005	He et al. (2018)	F1	82.5	# 15	Compare
Semantic Role Labeling	CoNLL 2005	He et al. (2018) + ELMo	F1	86.0	# 13	Compare
Semantic Role Labeling (predicted predicates)	CoNLL 2005	He et al. (2018)	F1	86.0	# 2	Compare
Semantic Role Labeling (predicted predicates)	CoNLL 2005	He et al. 2018	F1	82.5	# 5	Compare
Semantic Role Labeling (predicted predicates)	CoNLL 2012	He et al. 2018 + ELMo	F1	82.9	# 4	Compare
Semantic Role Labeling (predicted predicates)	CoNLL 2012	He et al. 2018	F1	79.8	# 7	Compare
Semantic Role Labeling	OntoNotes	He et al.,	F1	85.5	# 11	Compare
Semantic Role Labeling	OntoNotes	He et al.	F1	82.1	# 15	Compare

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Jointly Predicting Predicates and Arguments in Neural Semantic Role Labeling

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