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Geolm Base Toponym Recognition

Developed by zekun-li
GeoLM is a language model designed for detecting toponyms from sentences. It is pre-trained on global OpenStreetMap, WikiData, and Wikipedia data and fine-tuned on the GeoWebNews dataset.
Downloads 186
Release Time : 7/15/2023

Model Overview

This model is specifically designed for toponym detection tasks, capable of identifying geographic entity names from input sentences.

Model Features

Geospatial Understanding
The model is specially trained to understand geospatial concepts and toponym entities.
Multi-source Data Pre-training
Pre-trained on diverse geographic data sources including OpenStreetMap, WikiData, and Wikipedia.
Domain-specific Fine-tuning
Fine-tuned on the GeoWebNews specialized toponym dataset to optimize toponym recognition performance.

Model Capabilities

Toponym Entity Recognition
Geospatial Text Understanding
Token Classification

Use Cases

Geographic Information Systems
News Geographic Analysis
Extract geographic location information from news reports for geospatial analysis.
Social Media Geotagging
Identify geographic locations mentioned in social media content.
Data Annotation
Automated Geographic Data Annotation
Automatically annotate toponym entities for geographic datasets.
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