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 276–300 of 620 papers

TitleStatusHype
Deep Learning on Graphs for Natural Language Processing—0
Automatically Extracting Qualia Relations for the Rich Event Ontology—0
A General-Purpose Algorithm for Constrained Sequential Inference—0
Adaptive Convolution for Semantic Role Labeling—0
Deep Learning for Chinese Word Segmentation and POS Tagging—0
Deeper syntax for better semantic parsing—0
A Unified Architecture for Semantic Role Labeling and Relation Classification—0
Decomposing Bilexical Dependencies into Semantic and Syntactic Vectors—0
An incremental model of syntactic bootstrapping—0
Debugging Frame Semantic Role Labeling—0
Data-Driven Text Simplification—0
Auditing Deep Learning processes through Kernel-based Explanatory Models—0
DAHRS: Divergence-Aware Hallucination-Remediated SRL Projection—0
CVE-driven Attack Technique Prediction with Semantic Information Extraction and a Domain-specific Language Model—0
Attentive Semantic Role Labeling with Boundary Indicator—0
An Hymn of an even Deeper Sentiment Analysis—0
Inferring Selectional Preferences from Part-Of-Speech N-grams—0
Inference is Everything: Recasting Semantic Resources into a Unified Evaluation Framework—0
Inducing Semantic Representation from Text by Jointly Predicting and Factorizing Relations—0
CROWD-IN-THE-LOOP: A Hybrid Approach for Annotating Semantic Roles—0
Inducing Script Structure from Crowdsourced Event Descriptions via Semi-Supervised Clustering—0
Inducing Implicit Arguments from Comparable Texts: A Framework and Its Applications—0
Cross Sentence Inference for Process Knowledge—0
A System for Building FrameNet-like Corpus for the Biomedical Domain—0
Incremental Semantic Role Labeling with Tree Adjoining Grammar—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