awesome-repositories.com
Blog
MCP
awesome-repositories.com

Discover the best open-source repositories with AI-powered search.

ExploreCurated searchesOpen-source alternativesSelf-hosted softwareBlogSitemap
ProjectMCP serverAboutHow we rankPress
LegalPrivacyTerms
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
yyDing1 avatar

yyDing1/GNER

0
View on GitHub↗
60 stars·3 forks·Python·Apache-2.0·14 views

GNER

Rethinking Negative Instances for Generative Named Entity Recognition

Features

  • Cross-Domain Learning - Generative entity recognition with negative instance handling.
  • Instruction Tuning - Generative entity recognition with negative instance handling.
  • Named Entity Recognition - Generative approach addressing negative instances in entity recognition.

Star history

Star history chart for yyding1/gnerStar history chart for yyding1/gner

How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.

AI search

Explore more awesome repositories

Describe what you need in plain English — the AI ranks thousands of curated open-source projects by relevance.

Start searching with AI

Open-source alternatives to GNER

Similar open-source projects, ranked by how many features they share with GNER.
  • universal-ner/universal-neruniversal-ner avatar

    universal-ner/universal-ner

    375View on GitHub↗

    UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition Wenxuan Zhou, Sheng Zhang, Yu Gu, Muhao Chen, Hoifung Poon (*Equal Contribution)

    Python
    View on GitHub↗375
  • urchade/glinerurchade avatar

    urchade/GLiNER

    3,333View on GitHub↗

    Generalist and Lightweight Model for Named Entity Recognition (Extract any entity types from texts)

    Python
    View on GitHub↗3,333
  • emseoyk/verifineremseoyk avatar

    emseoyk/VerifiNER

    13View on GitHub↗

    Official code for ACL 2024 paper: VerifiNER: Verification-augmented NER via Knowledge-grounded Reasoning with Large Language Models.

    Python
    View on GitHub↗13
  • flairnlp/flairflairNLP avatar

    flairNLP/flair

    14,378View on GitHub↗

    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

    Python
    View on GitHub↗14,378
See all 30 alternatives to GNER→

Frequently asked questions

What does yyding1/gner do?

Rethinking Negative Instances for Generative Named Entity Recognition

What are the main features of yyding1/gner?

The main features of yyding1/gner are: Cross-Domain Learning, Instruction Tuning, Named Entity Recognition.

What are some open-source alternatives to yyding1/gner?

Open-source alternatives to yyding1/gner include: universal-ner/universal-ner — UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition Wenxuan Zhou, Sheng… urchade/gliner — Generalist and Lightweight Model for Named Entity Recognition (Extract any entity types from texts). emseoyk/verifiner — Official code for ACL 2024 paper: VerifiNER: Verification-augmented NER via Knowledge-grounded Reasoning with Large… 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…