MultiEL
Multilingual Entity Linking model by BELA model
This project want to create easy-to-use Multilingual Entity Linking model by BELA model.
**Origin Project**
- Bi-encoder Entity Linking Architecture (BELA): [https://github.com/facebookresearch/BELA](https://github.com/facebookresearch/BELA)
Install
> pip install multiel
Usage
python
from multiel import BELA
bela_run = BELA(device="cuda")
print(bela_run.process_batch(["นายกประยุทธ์ประกาศจัดการเลือกตั้ง"]))
output:
python
[{'offsets': [0], 'lengths': [12], 'entities': ['Q2108126'], 'md_scores': [0.22365164756774902], 'el_scores': [0.6967974901199341]}]
API
python
from multiel import BELA
BELA(
md_threshold:float=0.2,
el_threshold:float=0.4,
checkpoint_name: str="wiki",
device: str="cuda:0",
config_name:str="joint_el_mel_new",
repo:str="wannaphong/BELA"
)
- md_threshold: md threshold
- el_threshold: Entity Linking threshold
- checkpoint_name: checkpoint name (wiki, aida, mewsli, and e2e) or your file name with extension
- device: device
- config_name: config name (in the BELA project)
- repo: Huggingface Hub repo (Default [wannaphong/BELA](https://huggingface.co/wannaphong/BELA))
**Predict**
python
BELA.process_batch([str, str])
License
MIT license and the model is MIT license. ([BELA is MIT licensed](https://github.com/facebookresearch/BELA/blob/main/LICENSE))