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 376–400 of 620 papers

TitleStatusHype
UTA DLNLP at SemEval-2016 Task 1: Semantic Textual Similarity: A Unified Framework for Semantic Processing and Evaluation—0
Unsupervised Learning of Prototypical Fillers for Implicit Semantic Role Labeling—0
Grounded Semantic Role Labeling—0
Right-truncatable Neural Word Embeddings—0
Neural Semantic Role Labeling with Dependency Path EmbeddingsCode0
MEANTIME, the NewsReader Multilingual Event and Time Corpus—0
Towards Building Semantic Role Labeler for Indian Languages—0
Persian Proposition Bank—0
Semi-automatically Alignment of Predicates between Speech and OntoNotes data—0
Generating Training Data for Semantic Role Labeling based on Label Transfer from Linked Lexical Resources—0
Inducing Implicit Arguments from Comparable Texts: A Framework and Its Applications—0
Extra \~ao de Alvos em Coment\'arios de Not\' em Portugu\^es baseada na Teoria da Centraliza \~ao (Target Extraction in News Reviews in Portuguese based on Centering Theory)—0
VerbLexPor: um recurso l\'exico com anota \~ao de pap\'eis sem\^anticos para o portugu\^es (VerbLexPor: a lexical resource annotated with semantic roles for Portuguese)—0
Towards the Unsupervised Acquisition of Implicit Semantic Roles—0
Structural Alignment for Comparison Detection—0
Memory-Based Acquisition of Argument Structures and its Application to Implicit Role Detection—0
Identifying Key Concepts from EHR Notes Using Domain Adaptation—0
Semantic Framework for Comparison Structures in Natural Language—0
Any-language frame-semantic parsing—0
Question-Answer Driven Semantic Role Labeling: Using Natural Language to Annotate Natural Language—0
Hierarchical Recurrent Neural Network for Document Modeling—0
Distributed Representations for Unsupervised Semantic Role Labeling—0
Chinese Semantic Role Labeling with Bidirectional Recurrent Neural Networks—0
Semantic Role Labeling with Neural Network Factors—0
Joint A* CCG Parsing and Semantic Role Labelling—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