metadata
language:
- multilingual
- pl
- ru
- uk
- bg
- cs
- sl
datasets:
- SlavicNER
license: apache-2.0
library_name: transformers
pipeline_tag: text2text-generation
tags:
- entity linking
widget:
- text: pl:Polsce
- text: cs:Velké Británii
- text: bg:българите
- text: ru:Великобританию
- text: sl:evropske komisije
- text: uk:Європейського агентства лікарських засобів
Model description
This is a baseline model for named entity lemmatization trained on the single-out topic split of the SlavicNER corpus.
Usage
You can use this model directly with a pipeline for text2text generation:
from transformers import pipeline
model_name = "SlavicNLP/slavicner-linking-single-out-large"
pipe = pipeline("text2text-generation", model_name)
texts = ["pl:Polsce", "cs:Velké Británii", "bg:българите", "ru:Великобританию", "sl:evropske komisije",
"uk:Європейського агентства лікарських засобів"]
outputs = pipe(texts)
ids = [o['generated_text'] for o in outputs]
print(ids)
# ['GPE-Poland', 'GPE-Great-Britain', 'GPE-Bulgaria', 'GPE-Great-Britain', 'ORG-European-Commission', 'ORG-EMA-European-Medicines-Agency']