SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 176–200 of 620 papers

TitleStatusHype
LIMIT-BERT : Linguistic Informed Multi-Task BERT—0
Syntax-Enhanced Self-Attention-Based Semantic Role Labeling—0
Capturing Argument Interaction in Semantic Role Labeling with Capsule NetworksCode0
Robust Semantic Parsing with Adversarial Learning for Domain Generalization—0
Question Answering is a Format; When is it Useful?—0
Graph Convolutions over Constituent Trees for Syntax-Aware Semantic Role LabelingCode0
Subword ELMo—0
Reasoning Over Semantic-Level Graph for Fact Checking—0
Semantic Role Labeling with Iterative Structure RefinementCode0
Semantics-aware BERT for Language UnderstandingCode0
From Textual Information Sources to Linked Data in the Agatha Project—0
Automatic Propbank Generation for Turkish—0
Semantic Role Labeling with Pretrained Language Models for Known and Unknown Predicates—0
Dependency-Based Self-Attention for Transformer NMT—0
ULSAna: Universal Language Semantic Analyzer—0
Syntax-aware Multilingual Semantic Role LabelingCode0
Translate and Label! An Encoder-Decoder Approach for Cross-lingual Semantic Role LabelingCode0
Semantic Role Labeling with Associated Memory NetworkCode0
Domain Adaptation of SRL Systems for Biological Processes—0
Towards Universal Semantic Representation—0
Syntax-aware Neural Semantic Role LabelingCode0
Enhancing Opinion Role Labeling with Semantic-Aware Word Representations from Semantic Role LabelingCode0
How to best use Syntax in Semantic Role LabellingCode0
An Approach for Process Model Extraction By Multi-Grained Text ClassificationCode0
Graph Convolutional Network with Sequential Attention For Goal-Oriented Dialogue Systems—0
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All datasetsOntoNotesCoNLL 2005CoNLL05 BrownCoNLL05 WSJCoNLL12CoNLL-2009CoNLL-2012

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1HeSyFuF188.59—Unverified
2CRF2o + RoBERTaF188.32—Unverified
3MRC-SRLF188.3—Unverified
4ReCAT(pretrained on wikitext103)F188—Unverified
5SRL-MM + XLNetF187.67—Unverified
6CRF2o + BERTF187.66—Unverified
7RoBERTa+RegCCRFF187.51—Unverified
8RoBERTa+CRFF187.27—Unverified
9BiLSTM-Span (Ensemble)F187—Unverified
10BiLSTM-SpanF186.2—Unverified
#ModelMetricClaimedVerifiedStatus
1MRC-SRLF190—Unverified
2SRL-MM + XLNetF189.8—Unverified
3CRF2o + RoBERTaF189.54—Unverified
4HeSyFuF189.04—Unverified
5CRF2o + BERTF189.03—Unverified
6Mohammadshahi and Henderson (2021)F188.93—Unverified
7BiLSTM-Span (Ensemble, predicates given)F188.5—Unverified
8CRF2oF187.87—Unverified
9Li et al. (2019) (Ensemble)F187.7—Unverified
10BiLSTM-SpanF187.6—Unverified
#ModelMetricClaimedVerifiedStatus
1DeepStruct multi-task w/ finetuneF192.1—Unverified
2DeepStruct multi-taskF192—Unverified
#ModelMetricClaimedVerifiedStatus
1DeepStruct multi-taskF195.5—Unverified
2DeepStruct multi-task w/ finetuneF195.2—Unverified
#ModelMetricClaimedVerifiedStatus
1DeepStruct multi-taskF197.2—Unverified
2DeepStruct multi-task w/ finetuneF196—Unverified
#ModelMetricClaimedVerifiedStatus
1Ours (High-Order model)F1 (Arg.)90.2—Unverified
#ModelMetricClaimedVerifiedStatus
1HeSyFuAvg. F188.59—Unverified