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license: cc-by-4.0
language:
- de
size_categories:
- n<1K
---
# CO-Fun: Tokenized Sentences
This datasets hosts a sentence-tokenized version of the [CO-Fun: A German Dataset on Company Outsourcing in Fund Prospectuses for Named Entity Recognition and Relation Extraction](https://arxiv.org/abs/2403.15322) dataset.
## Creation
The following script can be used to reproduce the creation of the dataset:
```python
import flair
import json
from flair.datasets.sequence_labeling import ColumnCorpus
from flair.file_utils import cached_path
from pathlib import Path
from typing import Optional, Union
class NER_CO_FUNER(ColumnCorpus):
def __init__(
self,
base_path: Optional[Union[str, Path]] = None,
in_memory: bool = True,
**corpusargs,
) -> None:
base_path = flair.cache_root / "datasets" if not base_path else Path(base_path)
dataset_name = self.__class__.__name__.lower()
data_folder = base_path / dataset_name
data_path = flair.cache_root / "datasets" / dataset_name
columns = {0: "text", 2: "ner"}
hf_download_path = "https://huggingface.co/datasets/stefan-it/co-funer/resolve/main"
for split in ["train", "dev", "test"]:
cached_path(f"{hf_download_path}/{split}.tsv", data_path)
super().__init__(
data_folder,
columns,
in_memory=in_memory,
comment_symbol=None,
**corpusargs,
)
corpus = NER_CO_FUNER()
with open("./train.jsonl", "wt") as f_out:
for sentence in corpus.train:
current_example = {
"text": sentence.to_tokenized_string()
}
f_out.write(json.dumps(current_example) + "\n")
```
The extracted dataset has 758 sentences. |