Datasets:
Tasks:
Token Classification
Modalities:
Text
Formats:
json
Languages:
Serbian
Size:
10K - 100K
Tags:
NER
License:
license: cc-by-sa-4.0 | |
task_categories: | |
- token-classification | |
language: | |
- sr | |
pretty_name: SrpELTeC-gold-NER training dataset | |
size_categories: | |
- 100K<n<1M | |
tags: | |
- NER | |
Named Entity Recognition Training corpus for Serbian – The selection of 11 full novels and excerpts from 15 novels from Serbian literary corpus of novels written more than a century ago, have been automatically labelled with SrpNER system for Serbian in the first stage of the gold standard preparation. Contains 330.119 tokens, 7 classes: person, organization, location, event, work, demonym, role. | |
It is constituted of a single jsonl file that can be loaded via: | |
```python | |
from datasets import load_dataset | |
dataset = load_dataset("jerteh/SrpELTeC-gold-NER") | |
``` | |
Preview: | |
```python | |
ds = dataset["train"][36042] | |
for x, y, z in zip(ds["token"], ds["lemma"], ds["ner"]): | |
print(x, y, z) | |
Setila setiti O | |
se se O | |
da da O | |
je jesam O | |
Petrovski Petrovski B-EVENT | |
post post I-EVENT | |
. . O | |
``` | |
Citation: | |
```bibtex | |
@inproceedings{frontini2020named, | |
title={Named entity recognition for distant reading in ELTeC}, | |
author={Frontini, Francesca and Brando, Carmen and Byszuk, Joanna and Galleron, Ioana and Santos, Diana and Stankovi{\'c}, Ranka}, | |
booktitle={CLARIN Annual Conference 2020}, | |
year={2020} | |
} | |
``` |