Semantic Role Labeling

Semantic role labeling aims to model the predicate-argument structure of a sentence and is often described as answering "Who did what to whom". BIO notation is typically used for semantic role labeling.

Example:

| Housing | starts | are | expected | to | quicken | a | bit | from | August’s | pace | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | B-ARG1 | I-ARG1 | O | O | O | V | B-ARG2 | I-ARG2 | B-ARG3 | I-ARG3 | I-ARG3 |

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 371–380 of 620 papers

Title	Date	Tasks	Status
Instrument subjects without Instrument role	Apr 1, 2015	Semantic Role Labeling	—Unverified
Integer Linear Programming formulations in Natural Language Processing	Apr 1, 2017	Dependency ParsingNatural Language Inference	—Unverified
Integrating Generative Lexicon Event Structures into VerbNet	May 1, 2018	Semantic ParsingSemantic Role Labeling	—Unverified
Integrating Multiple Dependency Corpora for Inducing Wide-coverage Japanese CCG Resources	Aug 1, 2013	Dependency ParsingSemantic Role Labeling	—Unverified
Intermediary Semantic Representation through Proposition Structures	Jun 1, 2014	Dependency ParsingSemantic Parsing	—Unverified
Interpretable Semantic Role Relation Table for Supporting Facts Recognition of Reading Comprehension	Sep 29, 2021	Machine Reading ComprehensionReading Comprehension	—Unverified
Intrinsic Evaluations of Word Embeddings: What Can We Do Better?	Aug 1, 2016	Named Entity Recognition (NER)Semantic Role Labeling	—Unverified
InVeRo: Making Semantic Role Labeling Accessible with Intelligible Verbs and Roles	Oct 1, 2020	Semantic Role Labeling	—Unverified
InVeRo-XL: Making Cross-Lingual Semantic Role Labeling Accessible with Intelligible Verbs and Roles	Nov 1, 2021	Semantic Role LabelingSentence	—Unverified
Is Argument Structure of Learner Chinese Understandable: A Corpus-Based Analysis	Aug 17, 2023	Semantic Role Labeling	—Unverified

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All datasets OntoNotes CoNLL 2005 CoNLL05 Brown CoNLL05 WSJ CoNLL12 CoNLL-2009 CoNLL-2012

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	HeSyFu	F1	88.59	—	Unverified
2	CRF2o + RoBERTa	F1	88.32	—	Unverified
3	MRC-SRL	F1	88.3	—	Unverified
4	ReCAT(pretrained on wikitext103)	F1	88	—	Unverified
5	SRL-MM + XLNet	F1	87.67	—	Unverified
6	CRF2o + BERT	F1	87.66	—	Unverified
7	RoBERTa+RegCCRF	F1	87.51	—	Unverified
8	RoBERTa+CRF	F1	87.27	—	Unverified
9	BiLSTM-Span (Ensemble)	F1	87	—	Unverified
10	BiLSTM-Span	F1	86.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MRC-SRL	F1	90	—	Unverified
2	SRL-MM + XLNet	F1	89.8	—	Unverified
3	CRF2o + RoBERTa	F1	89.54	—	Unverified
4	HeSyFu	F1	89.04	—	Unverified
5	CRF2o + BERT	F1	89.03	—	Unverified
6	Mohammadshahi and Henderson (2021)	F1	88.93	—	Unverified
7	BiLSTM-Span (Ensemble, predicates given)	F1	88.5	—	Unverified
8	CRF2o	F1	87.87	—	Unverified
9	Li et al. (2019) (Ensemble)	F1	87.7	—	Unverified
10	BiLSTM-Span	F1	87.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DeepStruct multi-task w/ finetune	F1	92.1	—	Unverified
2	DeepStruct multi-task	F1	92	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DeepStruct multi-task	F1	95.5	—	Unverified
2	DeepStruct multi-task w/ finetune	F1	95.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DeepStruct multi-task	F1	97.2	—	Unverified
2	DeepStruct multi-task w/ finetune	F1	96	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Ours (High-Order model)	F1 (Arg.)	90.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	HeSyFu	Avg. F1	88.59	—	Unverified