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 226–250 of 620 papers

TitleStatusHype
Filling Conversation Ellipsis for Better Social Dialog Understanding—0
Cross-lingual alignment transfer: a chicken-and-egg story?—0
Findings of the CONSTRAINT 2022 Shared Task on Detecting the Hero, the Villain, and the Victim in Memes—0
Find the word that does not belong: A Framework for an Intrinsic Evaluation of Word Vector Representations—0
Fine-tuning and Sampling Strategies for Multimodal Role Labeling of Entities under Class Imbalance—0
First approach toward Semantic Role Labeling for Basque—0
First steps towards a Predicate Matrix—0
Focusing Annotation for Semantic Role Labeling—0
Forest Reranking through Subtree Ranking—0
Comparing Span Extraction Methods for Semantic Role Labeling—0
FrameFOR -- Uma Base de Conhecimento de Frames Sem\^anticos para Per\' de Inform\'atica (FrameFOR - a Knowledge Base of Semantic Frames for Digital Forensics)[In Portuguese]—0
FrameIt: Ontology Discovery for Noisy User-Generated Text—0
FrameNet on the Way to Babel: Creating a Bilingual FrameNet Using Wiktionary as Interlingual Connection—0
Frame-Semantic Role Labeling with Heterogeneous Annotations—0
Frame Semantics across Languages: Towards a Multilingual FrameNet—0
Framework of Semantic Role Assignment based on Extended Lexical Conceptual Structure: Comparison with VerbNet and FrameNet—0
FRASE: Structured Representations for Generalizable SPARQL Query Generation—0
Friend-training: Learning from Models of Different but Related Tasks—0
From Natural Language Specifications to Program Input Parsers—0
From Textual Information Sources to Linked Data in the Agatha Project—0
Concept-based Selectional Preferences and Distributional Representations from Wikipedia Articles—0
Generating Adequate Distractors for Multiple-Choice Questions—0
Generating High Quality Proposition Banks for Multilingual Semantic Role Labeling—0
Generating Training Data for Semantic Role Labeling based on Label Transfer from Linked Lexical Resources—0
Cross-Document Non-Fiction Narrative Alignment—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