README.md

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.

Resources and Technical Documentation

• Paper: Cross-lingual Named Entity Corpus for Slavic Languages, to appear in LREC-COLING 2024.
• Annotation guidelines: https://arxiv.org/pdf/2404.00482
• SlavicNER Corpus: https://github.com/SlavicNLP/SlavicNER

Evaluation

Language	Seq2seq	Support
PL	75.13	2 549
CS	77.92	1 137
RU	67.56	18 018
BG	63.60	6 085
SL	76.81	7 082
UK	58.94	3 085
All	68.75	37 956

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']

Citation

Will appear soon