snoop2head/KLUE-RBERT
↔️ Utilizing RBERT model structure for KLUE Relation Extraction task
This project helps identify and classify relationships between entities within Korean text. You input sentences with specific subjects and objects, and it outputs labels like 'person is employee of organization' or 'no relation'. This is useful for linguists, data analysts, or anyone working with Korean text to understand connections between people, organizations, and concepts.
No commits in the last 6 months.
Use this if you need to automatically extract and categorize relationships embedded in Korean language documents.
Not ideal if you are working with languages other than Korean, or if your primary goal is not relation extraction.
Stars
15
Forks
—
Language
Python
License
—
Category
Last pushed
Nov 15, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/snoop2head/KLUE-RBERT"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
davidsbatista/BREDS
"Bootstrapping Relationship Extractors with Distributional Semantics" (Batista et al., 2015) in...
davidsbatista/Snowball
Implementation with some extensions of the paper "Snowball: Extracting Relations from Large...
nicolay-r/AREkit
Document level Attitude and Relation Extraction toolkit (AREkit) for sampling and processing...
plkmo/BERT-Relation-Extraction
PyTorch implementation for "Matching the Blanks: Distributional Similarity for Relation Learning" paper
thunlp/FewRel
A Large-Scale Few-Shot Relation Extraction Dataset