Update README.md

README.md

@@ -1,14 +1,83 @@
 ---
-license: cc-by-4.0
+annotations_creators:
+- expert-generated
+language:
+- es
+language_creators:
+- expert-generated
+license:
+- cc-by-4.0
+multilinguality:
+- monolingual
+pretty_name: InferES
+size_categories:
+- 1K<n<10K
+source_datasets:
+- original
+tags:
+- nli
+- spanish
+- negation
+- coreference
+task_categories:
+- text-classification
+task_ids:
+- natural-language-inference
 ---
 
-# The INFERES dataset
+# Dataset Card for [Dataset Name]
+
+## Table of Contents
+- [Table of Contents](#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)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:** https://github.com/venelink/inferes
+- **Repository:** https://github.com/venelink/inferes
+- **Paper:** https://arxiv.org/abs/2210.03068
+- **Point of Contact:** venelin [at] utexas [dot] edu
+
+### Dataset Summary
+
+Natural Language Inference dataset for European Spanish
+
+Paper accepted and (to be) presented at COLING 2022
+
+### Supported Tasks and Leaderboards
+
+Natural Language Inference
+
+### Languages
+
+Spanish
+
+## Dataset Structure
+
+The dataset contains two texts inputs (Premise and Hypothesis), Label for three-way classification, and annotation data.
+
+### Data Instances
 
 train size = 6444 
 
 test size = 1612
 
-### Columns
+### Data Fields
 
 ID : the unique ID of the instance
 
@@ -22,13 +91,42 @@ Topic: 1 (Picasso), 2 (Columbus), 3 (Videogames), 4 (Olympic games), 5 (EU), 6 (
 
 Anno: ID of the annotators (in cases of undergrads or crowd - the ID of the group)
 
-Anno_Type: strategy used to generate the data: Generate, Rewrite, Crowd, and Automated
+Anno Type: Generate, Rewrite, Crowd, and Automated
+
+### Data Splits
+
+train size = 6444 
+
+test size = 1612
+
+The train/test split is stratified by a key that combines Label + Anno + Anno type
+
+### Source Data
+
+Wikipedia + text generated from "sentence generators" hired as part of the process
+
+#### Who are the annotators?
+
+Native speakers of European Spanish
 
-The train/test split is stratified by a key that combines Label + Anno + Anno_type
+### Personal and Sensitive Information
 
-### Disclaimer
+No personal or Sensitive information is included.
 
-The results in the paper are done via k-fold cross validation and average across multiple runs. Experiments with this split might differ slightly.
+Annotators are anonymized and only kept as "ID" for research purposes.
+
+### Dataset Curators
+
+Venelin Kovatchev
+
+### Licensing Information
 
-### License 
 cc-by-4.0
+
+### Citation Information
+
+To be added after proceedings from COLING 2022 appear
+
+### Contributions
+
+Thanks to [@venelink](https://github.com/venelink) for adding this dataset.