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Data and code for ACL 2023 Findings: Aligning Instruction Tasks Unlocks Large Language Models as Zero-Shot Relation Extractors.
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 is the codebase of the paper: ERA-CoT: Improving Chain-of-Thought through Entity Relationship Analysis.
The main features of oceanntwt/era-cot are: Relation Extraction, Zero-Shot Prompting.
Open-source alternatives to oceanntwt/era-cot include: sefeoglu/rag4re — -->. zjunlp/deepke — DeepKE is a knowledge extraction toolkit and framework designed to transform unstructured text into structured… qingwang-isu/augure — https://aclanthology.org/2023.emnlp-main.745.pdf. osu-nlp-group/qa4re — Data and code for ACL 2023 Findings: Aligning Instruction Tasks Unlocks Large Language Models as Zero-Shot Relation… microsoft/biogpt — BioGPT is a biomedical large language model and domain-specific transformer designed for processing and creating… declare-lab/relationprompt — The codes and dataset will be released soon!
