thunlp/Few-NERD
Code and data of ACL 2021 paper "Few-NERD: A Few-shot Named Entity Recognition Dataset"
This project offers a comprehensive dataset and code for training models to identify specific entities within text, even when very few examples are available. It helps researchers and AI practitioners develop and benchmark advanced named entity recognition (NER) systems. You input text, and the system outputs the identified entities categorized into fine-grained types like 'Art-Music' for 'London' in a musical context.
398 stars. No commits in the last 6 months.
Use this if you are an AI/NLP researcher or practitioner working on named entity recognition and need a robust dataset and baseline models for few-shot learning scenarios.
Not ideal if you are a non-technical user looking for an out-of-the-box solution to extract entities from your documents without delving into model training or dataset management.
Stars
398
Forks
54
Language
Python
License
Apache-2.0
Category
Last pushed
Sep 07, 2023
Commits (30d)
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