Update README.md

README.md

@@ -1,3 +1,108 @@
 ---
-license: cc-by-nc-sa-4.0
+annotations_creators:
+- expert-generated
+language:
+- sl
+language_creators:
+- found
+- expert-generated
+license:
+- cc-by-nc-sa-4.0
+multilinguality:
+- monolingual
+pretty_name: ssj500k
+size_categories:
+- 1K<n<10K
+- 10K<n<100K
+source_datasets: []
+tags:
+- ssj200k
+- ssj
+- fiction
+- non-fiction
+- news
+task_categories:
+- token-classification
+task_ids:
+- named-entity-recognition
+- part-of-speech
+- lemmatization
+- parsing
+- token-classification-other-semantic-role-labeling
+- token-classification-other-multiword-expression-detection
 ---
+
+# Dataset Card for ssj500k
+
+**Important**: there exists another HF implementation of the dataset ([classla/ssj500k](https://huggingface.co/datasets/classla/ssj500k)), but **this one is designed for more general use**. The CLASSLA version seems to expose only the specific training/validation/test annotations used in the CLASSLA library itself, for only a subset of examples. 
+
+### Dataset Summary
+
+The ssj500k training corpus contains about 500 000 tokens manually annotated on the levels of tokenization, sentence segmentation, morphosyntactic tagging, and lemmatization. It is also partially annotated for the following tasks:
+- named entity recognition (config `named_entity_recognition`)  
+- dependency parsing(*), Universal Dependencies style (config `dependency_parsing_ud`)  
+- dependency parsing, JOS/MULTEXT-East style (config `dependency_parsing_jos`)  
+- semantic role labeling (config `semantic_role_labeling`)  
+- multi-word expressions (config `multiword_expressions`)  
+
+If you want to load all the data along with their partial annotations, please use the config `all_data`.  
+
+\* _The UD dependency parsing labels are included here for completeness, but using the dataset [universal_dependencies](https://huggingface.co/datasets/universal_dependencies) should be preferred for dependency parsing applications to ensure you are using the most up-to-date data._  
+
+### Supported Tasks and Leaderboards
+
+Sentence tokenization, sentence segmentation, morphosyntactic tagging, lemmatization, named entity recognition, dependency parsing, semantic role labeling, multi-word expression detection.
+
+### Languages
+
+Slovenian.
+
+## Dataset Structure
+
+### Data Instances
+
+A sample instance from the dataset (using the config `all_data`):
+```
+TODO
+```
+
+### Data Fields
+
+TODO:
+- `attr_name`: a string doing something
+
+## Additional Information
+
+### Dataset Curators
+
+Simon Krek; et al. (please see http://hdl.handle.net/11356/1434 for the full list)
+
+### Licensing Information
+
+CC BY-NC-SA 4.0.
+
+### Citation Information
+
+The paper describing the dataset:
+```
+@InProceedings{krek2020ssj500k,
+title = {The ssj500k Training Corpus for Slovene Language Processing},
+author={Krek, Simon and Erjavec, Tomaž and Dobrovoljc, Kaja and Gantar, Polona and Arhar Holdt, Spela and Čibej, Jaka and Brank, Janez},
+booktitle={Proceedings of the Conference on Language Technologies and Digital Humanities},
+year={2020},
+pages={24-33}
+}
+```
+
+The resource itself:
+```
+@misc{krek2021clarinssj500k,
+title = {Training corpus ssj500k 2.3},
+author = {Krek, Simon and Dobrovoljc, Kaja and Erjavec, Toma{\v z} and Mo{\v z}e, Sara and Ledinek, Nina and Holz, Nanika and Zupan, Katja and Gantar, Polona and Kuzman, Taja and {\v C}ibej, Jaka and Arhar Holdt, {\v S}pela and Kav{\v c}i{\v c}, Teja and {\v S}krjanec, Iza and Marko, Dafne and Jezer{\v s}ek, Lucija and Zajc, Anja},
+url = {http://hdl.handle.net/11356/1434},
+year = {2021} }
+```
+
+### Contributions
+
+Thanks to [@matejklemen](https://github.com/matejklemen) for adding this dataset.