docs: add citation and arxiv link

README.md

@@ -54,7 +54,7 @@ task_ids:
 
 - **Homepage:** 
 - **Repository:** https://github.com/nala-cub/prost
-- **Paper:** 
+- **Paper:** https://arxiv.org/abs/2106.03634 
 - **Leaderboard:**
 - **Point of Contact:** [Stéphane Aroca-Ouellette](mailto:stephane.aroca-ouellette@colorado.edu)
 
@@ -158,12 +158,27 @@ PROST is designed to avoid models succeeding in unintended ways. First, PROST pr
 
 ### Licensing Information
 
-[More Information Needed]
+PROST is licensed under the Apache 2.0 license.
 
 ### Citation Information
 
-[More Information Needed]
+```
+@inproceedings{aroca-ouellette-etal-2021-prost,
+    title = "{PROST}: {P}hysical Reasoning about Objects through Space and Time",
+    author = "Aroca-Ouellette, St{\'e}phane  and
+      Paik, Cory  and
+      Roncone, Alessandro  and
+      Kann, Katharina",
+    booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
+    month = aug,
+    year = "2021",
+    address = "Online",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2021.findings-acl.404",
+    pages = "4597--4608",
+}
+```
 
 ### Contributions
 
-Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.
+Thanks to [@corypaik](https://github.com/corypaik) for adding this dataset.

dataset_infos.json

@@ -1 +1 @@
-{"default": {"description": "*Physical Reasoning about Objects Through Space and Time* (PROST) is a probing dataset to evaluate the ability of pretrained LMs to understand and reason about the physical world. PROST consists of 18,736 cloze-style multiple choice questions from 14 manually curated templates, covering 10 physical reasoning concepts:  direction, mass, height, circumference, stackable, rollable, graspable, breakable, slideable, and bounceable.\n", "citation": "", "homepage": "https://github.com/nala-cub/prost", "license": "Apache 2.0", "features": {"A": {"dtype": "string", "id": null, "_type": "Value"}, "B": {"dtype": "string", "id": null, "_type": "Value"}, "C": {"dtype": "string", "id": null, "_type": "Value"}, "D": {"dtype": "string", "id": null, "_type": "Value"}, "context": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "ex_question": {"dtype": "string", "id": null, "_type": "Value"}, "group": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 4, "names": ["A", "B", "C", "D"], "names_file": null, "id": null, "_type": "ClassLabel"}, "name": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "prost", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 5698256, "num_examples": 18736, "dataset_name": "prost"}}, "download_checksums": {"https://huggingface.co/datasets/corypaik/prost/resolve/main/data/default.jsonl": {"num_bytes": 7197063, "checksum": "05d773ae2768047579ea22415fc593199430747027b3df5621e60044fe893bde"}}, "download_size": 7197063, "post_processing_size": null, "dataset_size": 5698256, "size_in_bytes": 12895319}}
+{"default": {"description": "*Physical Reasoning about Objects Through Space and Time* (PROST) is a probing dataset to evaluate the ability of pretrained LMs to understand and reason about the physical world. PROST consists of 18,736 cloze-style multiple choice questions from 14 manually curated templates, covering 10 physical reasoning concepts:  direction, mass, height, circumference, stackable, rollable, graspable, breakable, slideable, and bounceable.\n", "citation": "@inproceedings{aroca-ouellette-etal-2021-prost,\n  title = \"{PROST}: {P}hysical Reasoning about Objects through Space and Time\",\n  author = \"Aroca-Ouellette, St{'e}phane  and\n    Paik, Cory  and\n    Roncone, Alessandro  and\n    Kann, Katharina\",\n  booktitle = \"Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021\",\n  month = aug,\n  year = \"2021\",\n  address = \"Online\",\n  publisher = \"Association for Computational Linguistics\",\n  url = \"https://aclanthology.org/2021.findings-acl.404\",\n  pages = \"4597--4608\",\n}\n", "homepage": "https://github.com/nala-cub/prost", "license": "Apache 2.0", "features": {"A": {"dtype": "string", "id": null, "_type": "Value"}, "B": {"dtype": "string", "id": null, "_type": "Value"}, "C": {"dtype": "string", "id": null, "_type": "Value"}, "D": {"dtype": "string", "id": null, "_type": "Value"}, "context": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "ex_question": {"dtype": "string", "id": null, "_type": "Value"}, "group": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 4, "names": ["A", "B", "C", "D"], "names_file": null, "id": null, "_type": "ClassLabel"}, "name": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "prost", "config_name": "default", "version": {"version_str": "1.0.1", "description": null, "major": 1, "minor": 0, "patch": 1}, "splits": {"test": {"name": "test", "num_bytes": 5698256, "num_examples": 18736, "dataset_name": "prost"}}, "download_checksums": {"https://huggingface.co/datasets/corypaik/prost/resolve/main/data/default.jsonl": {"num_bytes": 7197063, "checksum": "05d773ae2768047579ea22415fc593199430747027b3df5621e60044fe893bde"}}, "download_size": 7197063, "post_processing_size": null, "dataset_size": 5698256, "size_in_bytes": 12895319}}

prost.py

@@ -12,17 +12,33 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ==============================================================================
-"""TODO: Add a description here."""
-
+""" Physical Reasoning about Objects Through Space and Time (PROST)
+  
+  PROST is a probing dataset to evaluate the ability of pretrained LMs to 
+  understand and reason about the physical world. 
+"""
 import json
 import datasets
 
-# TODO: Add BibTeX citation
-# Find for instance the citation on arxiv or on the dataset repo/website
+
 _CITATION = """\
+@inproceedings{aroca-ouellette-etal-2021-prost,
+  title = "{PROST}: {P}hysical Reasoning about Objects through Space and Time",
+  author = "Aroca-Ouellette, St{\'e}phane  and
+    Paik, Cory  and
+    Roncone, Alessandro  and
+    Kann, Katharina",
+  booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
+  month = aug,
+  year = "2021",
+  address = "Online",
+  publisher = "Association for Computational Linguistics",
+  url = "https://aclanthology.org/2021.findings-acl.404",
+  pages = "4597--4608",
+}
 """
 
-# TODO: Add description of the dataset here
+
 _DESCRIPTION = """\
 *Physical Reasoning about Objects Through Space and Time* (PROST) is a probing dataset to evaluate the ability of pretrained LMs to understand and reason about the physical world. PROST consists of 18,736 cloze-style multiple choice questions from 14 manually curated templates, covering 10 physical reasoning concepts:  direction, mass, height, circumference, stackable, rollable, graspable, breakable, slideable, and bounceable.
 """
@@ -38,9 +54,8 @@ MC_LABELS = list('ABCD')
 
 
 class Prost(datasets.GeneratorBasedBuilder):
-  """TODO: Short description of my dataset."""
 
-  VERSION = datasets.Version('1.0.0')
+  VERSION = datasets.Version('1.0.1')
 
   def _info(self):
     features = datasets.Features({