How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.
CHisIEC: An Information Extraction Corpus for Ancient Chinese History
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 a meta-model distilled from ChatGPT-3.5-turbo for information extraction. This is an intermediate checkpoint that can be well-transferred to all kinds of downstream information extraction tasks.
Updates | Datasets | Models | Environment | Running | Results | Website | Paper
This is the implementation of filter-then-rerank pipeline in Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!. EMNLP'2023 (Findings).
The main features of mayubo2333/llm-ie are: Event Extraction, In Context Learning, Named Entity Recognition, Relation Extraction.
Projects with overlapping indexed features include: zjunlp/deepke — DeepKE is a knowledge extraction toolkit and framework designed to transform unstructured text into structured… tangxuemei1995/chisiec — CHisIEC: An Information Extraction Corpus for Ancient Chinese History. komeijiforce/metaie — This is a meta-model distilled from ChatGPT-3.5-turbo for information extraction. This is an intermediate checkpoint… jiangguochaogg/p-icl — Please save your dataset in data folder. Note that CoNLL2003 and WNUT2017 are open-source datasets, ACE2004 and… emma1066/self-improve-zero-shot-ner — This is the github repository for the paper to be appeared at NAACL 2024 main conference: Self-Improving for Zero-Shot… chen700564/metaner-icl — An implementation for ACL 2023 paper Learning In-context Learning for Named Entity Recognition.