Update README.md

README.md

@@ -1,4 +1,23 @@
 ---
+pretty_name: SAF - Legal Domain - German
+annotations_creators:
+- expert-generated
+language:
+- de
+language_creators:
+- other
+multilinguality:
+- monolingual
+size_categories:
+- 1K<n<10K
+source_datasets:
+- original
+tags:
+- short answer feedback
+- legal domain
+task_categories:
+- text2text-generation
+
 dataset_info:
   features:
   - name: id
@@ -18,21 +37,96 @@ dataset_info:
   - name: score
     dtype: float64
   splits:
-  - name: test_unseen_answers
-    num_bytes: 309580
-    num_examples: 221
-  - name: test_unseen_questions
-    num_bytes: 360672
-    num_examples: 275
   - name: train
     num_bytes: 2223070
     num_examples: 1596
   - name: validation
     num_bytes: 546759
     num_examples: 400
+  - name: test_unseen_answers
+    num_bytes: 309580
+    num_examples: 221
+  - name: test_unseen_questions
+    num_bytes: 360672
+    num_examples: 275
   download_size: 455082
   dataset_size: 3440081
 ---
+
 # Dataset Card for "saf_legal_domain_german"
 
-[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Additional Information](#additional-information)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+### Dataset Summary
+
+This Short Answer Feedback (SAF) dataset contains 19 German short answers in the domain of the German social law (with reference answers). The idea of constructing a bilingual (English and German) short answer dataset as a way to remedy the lack of content-focused feedback datasets was introduced in [Your Answer is Incorrect... Would you like to know why? Introducing a Bilingual Short Answer Feedback Dataset](https://aclanthology.org/2022.acl-long.587) (Filighera et al., ACL 2022). Please refer to the [saf_legal_domain_german](https://huggingface.co/datasets/JohnnyBoy00/saf_micro_job_german) and [saf_communication_networks_english](https://huggingface.co/datasets/JohnnyBoy00/saf_communication_networks_english) datasets for similarly constructed datasets that can be used for SAF.
+
+### Supported Tasks and Leaderboards
+
+- `short_answer_feedback`: The dataset can be used to train a Text2Text Generation model from HuggingFace transformers in order to generate automatic short answer feedback. 
+
+### Languages
+
+The questions, reference answers, provided answers and the answer feedback in the dataset are written in German.
+
+## Dataset Structure
+
+### Data Instances
+
+An example of an entry of the training split looks as follows.
+
+```
+{
+    "id": "1",
+    "question": "Ist das eine Frage?",
+    "reference_answer": "Ja, das ist eine Frage.",
+    "provided_answer": "Ich bin mir sicher, dass das eine Frage ist.",
+    "answer_feedback": "Korrekt.",
+    "verification_feedback": "Correct",
+    "error_class": "Keine",
+    "score": 1
+}
+```
+
+### Data Fields
+
+The data fields are the same among all splits.
+
+- `id`: a `string` feature (UUID4 in HEX format).
+- `question`: a `string` feature representing a question.
+- `reference_answer`: a `string` feature representing a reference answer to the question.
+- `provided_answer`: a `string` feature representing an answer that was provided for a particular question.
+- `answer_feedback`: a `string` feature representing the feedback given to the provided answers.
+- `verification_feedback`: a `string` feature representing an automatic labeling of the score. It can be `Correct` (`score` = 1), `Incorrect` (`score` = 0) or `Partially correct` (all intermediate scores).
+- `error_class`: a `string` feature representing the type of error identified in the case of a not completely correct answer.
+- `score`: a `float64` feature (between 0 and 1) representing the score given to the provided answer.
+
+### Data Splits
+
+The dataset is comprised of four data splits.
+
+- `train`: used for training, contains a set of questions and the provided answers to them.
+- `validation`: used for validation, contains a set of questions and the provided answers to them (derived from the original training set from which the data came from).
+- `test_unseen_answers`: used for testing, contains unseen answers to the questions present in the `train` split.
+- `test_unseen_questions`: used for testing, contains unseen questions that do not appear in the `train` split.
+
+|   Split           |train|validation|test_unseen_answers|test_unseen_questions|
+|-------------------|----:|---------:|------------------:|--------------------:|
+|Number of instances| 1596|       400|                221|                  275|
+
+## Additional Information
+
+### Contributions
+Thanks to [@JohnnyBoy2103](https://github.com/JohnnyBoy2103) for adding this dataset.