We provide an implementation of GCD that is compatible with the popular Transformers library!
The main features of epfl-dlab/gcd are: Information Extraction Frameworks.
Open-source alternatives to epfl-dlab/gcd include: zjunlp/deepke — DeepKE is a knowledge extraction toolkit and framework designed to transform unstructured text into structured… bids-xu-lab/bioner-llama — This repository contains the code and resources accompanying the paper titled "Advancing Entity Recognition in… cocacola-lab/collabkg — CollabKG is an open-source IE annotation toolkit that unifies NER, RE, and EE tasks, integrates KG and EKG, and… d-gurgurov/injecting-commonsense-knowledge-into-llms — Project Overview:. derekmma/dice — Source code and data for ACL 2023 main conference paper DICE: Data-Efficient Clinical Event Extraction with Generative… arkhn/bio-nlp2023 — This project is the codebase used for our weak supervision experiments using E3C dataset annotated with InstructGPT-3…
DeepKE is a knowledge extraction toolkit and framework designed to transform unstructured text into structured knowledge graphs. It provides a pipeline for identifying and classifying named entities, semantic relations, and events, converting raw datasets into structured triples. The project utilizes large language models as tool callers through a standardized context protocol to drive automated data extraction processes. It supports schema-driven extraction across multiple domains and bilingual text, employing joint entity and relation extraction to identify components in a single structured
This repository contains the code and resources accompanying the paper titled "Advancing Entity Recognition in Biomedicine via Instruction Tuning of Large Language Models." The paper explores the use of instruction-based learning paradigm to transform biomedical Named Entity Recognition (NER)…
CollabKG is an open-source IE annotation toolkit that unifies NER, RE, and EE tasks, integrates KG and EKG, and supports both English and Chinese languages. - CollabKG combines automatic and manual labeling to build a learnable human-machine cooperative system. In particular, humans benefit from…
This project is the codebase used for our weak supervision experiments using E3C dataset annotated with InstructGPT-3 and dictionary.