update script and data card

P3.py

@@ -12,7 +12,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-"""P3"""
+"""P3 (Public Pool of Prompts)"""
 
 
 import datasets
@@ -27,7 +27,7 @@ _CITATION = """\
 TODO"""
 
 _DESCRIPTION = """\
-P3 is a collection of prompted English datasets covering a diverse set of NLP tasks. A prompt is the combination of an input template and a target template. The templates are functions mapping a data example into natural language for the input and target sequences. For example, in the case of an NLI dataset, the data example would include fields for *Premise, Hypothesis, Label*. An input template would be *If {Premise} is true, is it also true that {Hypothesis}?*, whereas a target template can be defined with the label choices *Choices[label]*. Here *Choices* is prompt-specific metadata that consists of the options *yes, maybe, no* corresponding to *label* being entailment (0), neutral (1) or contradiction (2).
+P3 (Pubic Pool of Prompts)is a collection of prompted English datasets covering a diverse set of NLP tasks. A prompt is the combination of an input template and a target template. The templates are functions mapping a data example into natural language for the input and target sequences. For example, in the case of an NLI dataset, the data example would include fields for *Premise, Hypothesis, Label*. An input template would be *If {Premise} is true, is it also true that {Hypothesis}?*, whereas a target template can be defined with the label choices *Choices[label]*. Here *Choices* is prompt-specific metadata that consists of the options *yes, maybe, no* corresponding to *label* being entailment (0), neutral (1) or contradiction (2).
 
 Prompts are collected using [Promptsource](https://github.com/bigscience-workshop/promptsource), an interface to interactively write prompts on datasets, and collect prompt-specific metadata such as evaluation metrics. As of October 13th, there are 2'000 prompts collected for 270+ data(sub)sets. The collection of prompts is publicly available on [Promptsource](https://github.com/bigscience-workshop/promptsource).
 
@@ -83,8 +83,6 @@ def find_task_splits_and_features():
     """Find the available tasks under ./data and their available splits and features."""
     task_and_their_splits = defaultdict(dict)
     for stats in glob.glob(f"{_DATA_PATH}/*/stats.*.json"):
-        if "anli" not in stats:
-            continue
         folder_path = os.path.dirname(stats)
         task_name = folder_path.split("/")[-1]
         split_name = os.path.basename(stats).split(".")[1]

README.md

@@ -32,13 +32,7 @@ task_categories:
   - [Curation Rationale](#curation-rationale)
   - [Source Data](#source-data)
   - [Annotations](#annotations)
-  - [Personal and Sensitive Information](#personal-and-sensitive-information)
-- [Considerations for Using the Data](#considerations-for-using-the-data)
-  - [Social Impact of Dataset](#social-impact-of-dataset)
-  - [Discussion of Biases](#discussion-of-biases)
-  - [Other Known Limitations](#other-known-limitations)
 - [Additional Information](#additional-information)
-  - [Dataset Curators](#dataset-curators)
   - [Licensing Information](#licensing-information)
   - [Citation Information](#citation-information)
   - [Contributions](#contributions)
@@ -183,6 +177,8 @@ The main annotation guideline was that prompts needed to be grammatical and unde
 
 The full annotation given to the contributors can be found [here](https://github.com/bigscience-workshop/promptsource/blob/main/CONTRIBUTING.md). *Note to self: the link is currently being updated with the)
 
+## Additional Information
+
 ### Licensing Information
 
 The dataset is released under Apache 2.0.