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
The Role of Semantic Parsing in Understanding Procedural Text
In this paper, we investigate whether symbolic semantic representations, extracted from deep semantic parsers, can help reasoning over the states of involved entities in a procedural text.
Query Your Model with Definitions in FrameNet: An Effective Method for Frame Semantic Role Labeling
Such methods usually model role classification as naive multi-class classification and treat arguments individually, which neglects label semantics and interactions between arguments and thus hindering performance and generalization of models.
Semantic Role Labeling Meets Definition Modeling: Using Natural Language to Describe Predicate-Argument Structures
sapienzanlp/gsrl
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One of the common traits of past and present approaches for Semantic Role Labeling (SRL) is that they rely upon discrete labels drawn from a predefined linguistic inventory to classify predicate senses and their arguments.
What do you MEME? Generating Explanations for Visual Semantic Role Labelling in Memes
LCS2-IIITD/LUMEN-Explaining-Memes
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Here, we introduce a novel task - EXCLAIM, generating explanations for visual semantic role labeling in memes.
Influence Functions for Sequence Tagging Models
successar/segment_influence_functions
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We show the practical utility of segment influence by using the method to identify systematic annotation errors in two named entity recognition corpora.
PriMeSRL-Eval: A Practical Quality Metric for Semantic Role Labeling Systems Evaluation
In this paper, we address key practical issues with existing evaluation scripts and propose a more strict SRL evaluation metric PriMeSRL.
Astock: A New Dataset and Automated Stock Trading based on Stock-specific News Analyzing Model
jinanzou/astock
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In addition, we propose a self-supervised learning strategy based on SRLP to enhance the out-of-distribution generalization performance of our system.
GENEVA: Benchmarking Generalizability for Event Argument Extraction with Hundreds of Event Types and Argument Roles
We utilize this ontology to further introduce GENEVA, a diverse generalizability benchmarking dataset comprising four test suites, aimed at evaluating models' ability to handle limited data and unseen event type generalization.
DeepStruct: Pretraining of Language Models for Structure Prediction
cgraywang/deepstruct
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Findings (ACL) 2022
We introduce a method for improving the structural understanding abilities of language models.
Transition-based Semantic Role Labeling with Pointer Networks
Semantic role labeling (SRL) focuses on recognizing the predicate-argument structure of a sentence and plays a critical role in many natural language processing tasks such as machine translation and question answering.
