|
---
|
|
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](https://github.com/SlavicNLP/SlavicNER).
|
|
|
|
|
|
# Usage
|
|
|
|
You can use this model directly with a pipeline for text2text generation:
|
|
|
|
```python
|
|
from transformers import pipeline
|
|
|
|
model_name = "SlavicNLP/slavicner-linking-cross-topic-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']
|
|
```
|
|
|
