docs: add initial version

README.md

@@ -1,3 +1,65 @@
----
-license: mit
----
+---
+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.