S

Srl En Mbert Base

Developed by liaad
This model is a bert-base-multilingual-cased model fine-tuned on English CoNLL-formatted OntoNotes v5.0 semantic role labeling data, primarily used for semantic role labeling tasks.
Downloads 93
Release Time : 3/2/2022

Model Overview

This is a fine-tuned multilingual BERT model specifically designed for English Semantic Role Labeling (SRL) tasks. It can identify predicates and their related arguments in sentences, providing structured information for natural language understanding.

Model Features

Multilingual Foundation
Fine-tuned from bert-base-multilingual-cased model with multilingual understanding capabilities
Specialized for English SRL
Optimized specifically for English semantic role labeling tasks
Research Project Outcome
Developed as part of a research project and released alongside various other SRL models

Model Capabilities

Semantic Role Labeling
Natural Language Understanding
Predicate-Argument Structure Recognition

Use Cases

Natural Language Processing
Semantic Role Analysis
Analyze predicate-argument relationships in sentences
F1 score of 63.07 (PropBank.Br)
Cross-domain Semantic Analysis
Perform semantic role labeling on texts from different domains
F1 score of 58.56 (Buscapé dataset)
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