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Ner Dutch

Developed by flair
Flair's standard 4-class NER model for Dutch, used to identify person names, location names, organization names, and other names in Dutch text.
Downloads 74
Release Time : 3/2/2022

Model Overview

This is a sequence labeling model based on Transformer embeddings and LSTM-CRF, specifically designed for Dutch text named entity recognition tasks.

Model Features

High accuracy
Achieves an F1 score of 92.58 on the CoNLL-03 dataset
Multi-category recognition
Can identify 4 entity types: person names (PER), location names (LOC), organization names (ORG), and other names (MISC)
Transformer-based
Uses advanced Transformer embedding technology to improve recognition accuracy

Model Capabilities

Dutch text processing
Named entity recognition
Sequence labeling

Use Cases

Text analysis
News article entity extraction
Extract person names, location names, and organization names from Dutch news articles
Accurately identifies various entities in the text
Document processing
Process named entities in Dutch documents
Automatically annotates key information in documents
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