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 551–560 of 620 papers

Title	Date	Tasks	Status
Assorted, Archetypal and Annotated Two Million (3A2M) Cooking Recipes Dataset based on Active Learning	Mar 27, 2023	Active LearningGenre classification	—Unverified
Argument Inference from Relevant Event Mentions in Chinese Argument Extraction	Aug 1, 2013	Semantic Role Labeling	—Unverified
A Progressive Learning Approach to Chinese SRL Using Heterogeneous Data	Jul 1, 2017	Chinese Semantic Role LabelingMachine Translation	—Unverified
A Study of Imitation Learning Methods for Semantic Role Labeling	Nov 1, 2016	Imitation LearningSemantic Role Labeling	—Unverified
A Study on Bootstrapping Bilingual Vector Spaces from Non-Parallel Data (and Nothing Else)	Oct 1, 2013	Information RetrievalMachine Translation	—Unverified
The Dependency-Parsed FrameNet Corpus	May 1, 2012	Dependency ParsingPOS	—Unverified
A System for Building FrameNet-like Corpus for the Biomedical Domain	Apr 1, 2014	Question AnsweringSemantic Role Labeling	—Unverified
Applying Collocation Segmentation to the ACL Anthology Reference Corpus	Jul 1, 2012	Language ModellingMachine Translation	—Unverified
Attentive Semantic Role Labeling with Boundary Indicator	Sep 8, 2018	Semantic Role LabelingSentence	—Unverified
Auditing Deep Learning processes through Kernel-based Explanatory Models	Nov 1, 2019	Deep LearningSemantic 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