omarmhaimdat/quickner
Quickner is a new tool to quickly annotate texts for NER (Named Entity Recognition). It is written in Rust and accessible through a Python API.
This tool helps data scientists and NLP practitioners quickly label text data for Named Entity Recognition (NER). You provide raw text documents and a list of entities (like names, organizations, or locations) you want to find. The output is your original texts with the specified entities highlighted and categorized, which can then be used to train custom NLP models.
No commits in the last 6 months.
Use this if you need a simple, fast, and configurable way to annotate unstructured text data with specific entity types to prepare it for machine learning tasks.
Not ideal if you require a sophisticated human-in-the-loop annotation interface or collaborative labeling features, as this is primarily an automated programmatic tool.
Stars
21
Forks
1
Language
Rust
License
MPL-2.0
Category
Last pushed
Feb 24, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/omarmhaimdat/quickner"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
MantisAI/nervaluate
Full named-entity (i.e., not tag/token) evaluation metrics based on SemEval’13
dice-group/gerbil
GERBIL - General Entity annotatoR Benchmark
bltlab/seqscore
SeqScore: Scoring for named entity recognition and other sequence labeling tasks
syuoni/eznlp
Easy Natural Language Processing
LHNCBC/metamaplite
A near real-time named-entity recognizer