Create README.md

README.md

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+---
+license: cc-by-4.0
+task_categories:
+- text-classification
+language:
+- de
+pretty_name: GAHD
+---
+
+**NOTE** README copied from https://github.com/jagol/gahd
+
+This repository contains the dataset from our NAACL 2024 paper "Improving Adversarial Data Collection by Supporting Annotators: Lessons from GAHD, a German Hate Speech Dataset".
+
+`gahd.csv` contains the following columns:
+- `gahd_id`: unique identifier of the entry
+- `text`: text of the entry
+- `label`: `0` = "not-hate speech", `1` = "hate speech"
+- `round`: round in which the entry was created
+- `split`: "train", "dev", or "test"
+- `contrastive_gahd_id`: `gahd_id` of its contrastive example
+
+`gahd_disaggregated.csv` contains the following additional columns:
+- `source`: 
+    - if annotators entered the entry via the Dynabench interface: `dynabench`
+    - if the entry was translated from the Vidgen et al. 2021 dataset: `translation` 
+    - if the entry stems from the Leipzit news corpus: `news`
+- `model_prediction`: label predicted by the target model, `0` or `1`
+- `annotator_id`: unique identifier of the annotator that created the entry
+- `annotator_labels`: a string containing a forward slash-separated list of all labels by annotators
+- `expert_labels`: `0` or `1` if an expert annotator annotated the entry, otherwise empty
+
+When using GAHD, please cite our preprint on Arxiv:
+```
+@misc{goldzycher2024improving,
+      title={Improving Adversarial Data Collection by Supporting Annotators: Lessons from GAHD, a German Hate Speech Dataset}, 
+      author={Janis Goldzycher and Paul Röttger and Gerold Schneider},
+      year={2024},
+      eprint={2403.19559},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```