DFKI-NLP/DISTRE
[ACL 19] Fine-tuning Pre-Trained Transformer Language Models to Distantly Supervised Relation Extraction
This project helps Natural Language Processing (NLP) researchers and data scientists extract relationships between entities (like people, organizations, or locations) from large text datasets. It takes a collection of text documents and a list of known relationships, then trains a model to automatically identify similar relationships in new, unseen text. The output is a highly accurate model capable of performing automated relation extraction.
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Use this if you are an NLP researcher or data scientist working on distantly supervised relation extraction and need a robust, fine-tuned transformer model for your task.
Not ideal if you are a business user looking for a no-code solution to extract information from documents, or if you don't have experience with Python, PyTorch, or AllenNLP.
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Python
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Apache-2.0
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Jun 18, 2024
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