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
Identifying Key Concepts from EHR Notes Using Domain Adaptation—0
Identifying Pronominal Verbs: Towards Automatic Disambiguation of the Clitic `se' in Portuguese—0
Explicit Contextual Semantics for Text Comprehension—0
Hierarchical Multitask Learning with Dependency Parsing for Japanese Semantic Role Labeling Improves Performance of Argument Identification—0
ImpAr: A Deterministic Algorithm for Implicit Semantic Role Labelling—0
Implicit Semantic Roles in a Multilingual Setting—0
Improved Lexical Acquisition through DPP-based Verb Clustering—0
Handling Ambiguities of Bilingual Predicate-Argument Structures for Statistical Machine Translation—0
Corpora Annotated with Negation: An Overview—0
Improving Chinese-English PropBank Alignment—0
Improving Chinese Semantic Role Labeling using High-quality Surface and Deep Case Frames—0
Assessing the performance of Olelo, a real-time biomedical question answering application—0
Improving Implicit Semantic Role Labeling by Predicting Semantic Frame Arguments—0
Improving Japanese semantic-role-labeling performance with transfer learning as case for limited resources of tagged corpora on aggregated language—0
Improving NLP through Marginalization of Hidden Syntactic Structure—0
Improving Statistical Machine Translation with Selectional Preferences—0
Improving the Recall of a Discourse Parser by Constraint-based Postprocessing—0
Improving Unsupervised Question Answering via Summarization-Informed Question Generation—0
Incremental Semantic Role Labeling with Tree Adjoining Grammar—0
Inducing Implicit Arguments from Comparable Texts: A Framework and Its Applications—0
Inducing Script Structure from Crowdsourced Event Descriptions via Semi-Supervised Clustering—0
Inducing Semantic Representation from Text by Jointly Predicting and Factorizing Relations—0
Inference is Everything: Recasting Semantic Resources into a Unified Evaluation Framework—0
Integer Linear Programming formulations in Natural Language Processing—0
Grounding Semantic Roles in Images—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