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YFR718 avatar

YFR718/LTNER

0
View on GitHub↗
7 stars·0 forks·Python·6 views

LTNER

Large Language Model Tagging for Named Entity Recognition with Contextualized Entity Marking

Features

  • In Context Learning - Contextualized entity marking for improved tagging performance.
  • Named Entity Recognition - Contextualized entity marking for language model tagging.

Star history

Star history chart for yfr718/ltnerStar history chart for yfr718/ltner

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.

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Projects sharing features with LTNER

These projects share indexed features with LTNER. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • chen700564/metaner-iclchen700564 avatar

    chen700564/metaner-icl

    40View on GitHub↗

    An implementation for ACL 2023 paper Learning In-context Learning for Named Entity Recognition

    Python
    View on GitHub↗40
  • emma1066/self-improve-zero-shot-nerEmma1066 avatar

    Emma1066/Self-Improve-Zero-Shot-NER

    53View on GitHub↗

    This is the github repository for the paper to be appeared at NAACL 2024 main conference: Self-Improving for Zero-Shot Named Entity Recognition with Large Language Models.

    Python
    View on GitHub↗53
  • allenai/beaconallenai avatar

    allenai/beacon

    14View on GitHub↗

    This repository contains code to run the inference and evaluation of NER as described in our NAACL 2024 paper: On-the-fly Definition Augmentation of LLMs for Biomedical NER

    Python
    View on GitHub↗14
  • jiangguochaogg/p-icljiangguochaoGG avatar

    jiangguochaoGG/P-ICL

    7View on GitHub↗

    Please save your dataset in data folder. Note that CoNLL2003 and WNUT2017 are open-source datasets, ACE2004 and ACE2005 are not free. We keep our CoNLL2003 and WNUT2017 train and test JSON files in data folder.

    Python
    View on GitHub↗7
Compare all 30 related projects→

Frequently asked questions

What does yfr718/ltner do?

Large Language Model Tagging for Named Entity Recognition with Contextualized Entity Marking

What are the main features of yfr718/ltner?

The main features of yfr718/ltner are: In Context Learning, Named Entity Recognition.

Which projects share features with yfr718/ltner?

Projects with overlapping indexed features include: 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… lfoppiano/matsci-lumen — Code, data, and results described in the paper "Mining experimental data from materials science literature with large… allenai/beacon — This repository contains code to run the inference and evaluation of NER as described in our NAACL 2024 paper:… chen700564/metaner-icl — An implementation for ACL 2023 paper Learning In-context Learning for Named Entity Recognition. jiangguochaogg/p-icl — Please save your dataset in data folder. Note that CoNLL2003 and WNUT2017 are open-source datasets, ACE2004 and… mayubo2333/llm-ie — This is the implementation of filter-then-rerank pipeline in Large Language Model Is Not a Good Few-shot Information…