全局指针统一处理嵌套与非嵌套NER。
Die Hauptfunktionen von bojone/globalpointer sind: Named Entity Recognition.
Open-Source-Alternativen zu bojone/globalpointer sind unter anderem: flairnlp/flair — Flair is a transformer-based natural language processing framework used to build and train models for text… zalandoresearch/flair — Flair is a natural language processing framework for training and applying models for sequence labeling and text… llmware-ai/llmware — llmware is a Python framework for AI agent orchestration and model management, designed to coordinate multi-model… chen700564/metaner-icl — An implementation for ACL 2023 paper Learning In-context Learning for Named Entity Recognition. emseoyk/verifiner — Official code for ACL 2024 paper: VerifiNER: Verification-augmented NER via Knowledge-grounded Reasoning with Large… 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…
Flair is a transformer-based natural language processing framework used to build and train models for text classification and sequence tagging. It provides a specialized library for generating contextual text embeddings and performing linguistic analysis. The framework includes dedicated tools for named entity recognition, including the identification of specialized biomedical entities across multiple languages. It further supports entity linking to map identified text mentions to unique entries within general or biomedical knowledge bases. The project covers a broad range of language analys
Flair is a natural language processing framework for training and applying models for sequence labeling and text classification. It provides a system for generating word embeddings and identifying semantic entities within text. The framework includes a dedicated system for zero and few-shot learning, enabling text classification and entity extraction using minimal training examples by leveraging pre-trained knowledge. Its capabilities cover named entity recognition, sentiment analysis, and the training of specialized models using custom datasets. It also includes tooling for the visual highl
llmware is a Python framework for AI agent orchestration and model management, designed to coordinate multi-model workflows and autonomous agents. It provides a unified model catalog and standardized interface to execute specialized language models for complex research, analysis, and structured data generation. The project distinguishes itself through its heavy emphasis on local execution and quantized inference, allowing models to run on private infrastructure using CPU, GPU, and NPU acceleration via runtimes like ONNX and OpenVino. It features a specialized ability to translate natural lang
An implementation for ACL 2023 paper Learning In-context Learning for Named Entity Recognition