Semantic Role Labeling
132 papers with code • 7 benchmarks • 14 datasets
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 |
Benchmarks
These leaderboards are used to track progress in Semantic Role Labeling
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Datasets
FrameNet
OntoNotes 5.0
NomBank
QA-SRL
QA-SRL Bank 2.0
X-SRL
Latest papers
MuCPAD: A Multi-Domain Chinese Predicate-Argument Dataset
1) Based on a frame-free annotation methodology, we avoid writing complex frames for new predicates.
A Structured Span Selector
lyutyuh/structured-span-selector
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NAACL 2022
Many natural language processing tasks, e. g., coreference resolution and semantic role labeling, require selecting text spans and making decisions about them.
ATP: AMRize Then Parse! Enhancing AMR Parsing with PseudoAMRs
chenllliang/atp
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Findings (NAACL) 2022
As Abstract Meaning Representation (AMR) implicitly involves compound semantic annotations, we hypothesize auxiliary tasks which are semantically or formally related can better enhance AMR parsing.
Zero-shot Cross-lingual Conversational Semantic Role Labeling
hahahawu/zero-shot-xcsrl
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Findings (NAACL) 2022
While conversational semantic role labeling (CSRL) has shown its usefulness on Chinese conversational tasks, it is still under-explored in non-Chinese languages due to the lack of multilingual CSRL annotations for the parser training.
Fast and Accurate End-to-End Span-based Semantic Role Labeling as Word-based Graph Parsing
zslin177/srl-as-gp
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COLING 2022
Moreover, we propose a simple constrained Viterbi procedure to ensure the legality of the output graph according to the constraints of the SRL structure.
Semantic Role Labeling as Dependency Parsing: Exploring Latent Tree Structures Inside Arguments
yzhangcs/crfsrl
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COLING 2022
Semantic role labeling (SRL) is a fundamental yet challenging task in the NLP community.
Text Simplification for Comprehension-based Question-Answering
Text simplification is the process of splitting and rephrasing a sentence to a sequence of sentences making it easier to read and understand while preserving the content and approximating the original meaning.
A Graph-Based Neural Model for End-to-End Frame Semantic Parsing
ch4osmy7h/framenetparser
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EMNLP 2021
The three subtasks are closely related while previous studies model them individually, which ignores their intern connections and meanwhile induces error propagation problem.
Finding a Balanced Degree of Automation for Summary Evaluation
In this work, we propose flexible semiautomatic to automatic summary evaluation metrics, following the Pyramid human evaluation method.
CSAGN: Conversational Structure Aware Graph Network for Conversational Semantic Role Labeling
Conversational semantic role labeling (CSRL) is believed to be a crucial step towards dialogue understanding.
