changes

README.md

@@ -1,4 +1,23 @@
-<p align="center"><img src="https://huggingface.co/datasets/surrey-nlp/PLOD-unfiltered/blob/main/imgs/plod.png" alt="logo" width="50" height="84"/></p>
+annotations_creators:
+- Leonardo Zilio, Hadeel Saadany, Prashant Sharma, Diptesh Kanojia, Constantin Orasan 
+language_creators:
+- found
+languages:
+- en
+licenses:
+- cc-by-sa4.0
+multilinguality:
+- monolingual
+paperswithcode_id: acronym-identification
+pretty_name: 'PLOD: An Abbreviation Detection Dataset'
+size_categories:
+- 100K<n<1M
+source_datasets:
+- original
+task_categories:
+- token-classification
+task_ids:
+- named-entity-recognition
 
 # PLOD: An Abbreviation Detection Dataset  
 
@@ -12,6 +31,108 @@ We provide two variants of our dataset - Filtered and Unfiltered. They are descr
 
 2. The Unfiltered version can be accessed via [Huggingface Datasets here](https://huggingface.co/datasets/surrey-nlp/PLOD-unfiltered) and a [CONLL format is present here](https://github.com/surrey-nlp/PLOD-AbbreviationDetection).<br/>
 
+# Dataset Card for PLOD-unfiltered
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-instances)
+  - [Data Splits](#data-instances)
+- [Dataset Creation](#dataset-creation)
+  - [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)
+
+## Dataset Description
+
+- **Homepage:** [Needs More Information]
+- **Repository:** https://github.com/surrey-nlp/PLOD-AbbreviationDetection
+- **Paper:** XX
+- **Leaderboard:** YY
+- **Point of Contact:** [Diptesh Kanojia](mailto:[email protected])
+
+### Dataset Summary
+
+This PLOD Dataset is an English-language dataset of abbreviations and their long-forms tagged in text. The dataset has been collected for research from the PLOS journals indexing of abbreviations and long-forms in the text. This dataset was created to support the Natural Language Processing task of abbreviation detection and covers the scientific domain. 
+
+### Supported Tasks and Leaderboards
+
+This dataset primarily supports the Abbreviation Detection Task. It has also been tested on a train+dev split provided by the Acronym Detection Shared Task organized as a part of the Scientific Document Understanding (SDU) workshop at AAAI 2022.
+
+
+### Languages
+
+English
+
+## Dataset Structure
+
+### Data Instances
+
+A typical data point comprises an ID, a set of `tokens` present in the text, a set of `pos_tags` for the corresponding tokens obtained via Spacy NER, and a set of `ner_tags` which are limited to `AC` for `Acronym` and `LF` for `long-forms`.
+
+An example from the dataset:
+{'id': '1',
+ 'tokens': ['Study', '-', 'specific', 'risk', 'ratios', '(', 'RRs', ')', 'and', 'mean', 'BW', 'differences', 'were', 'calculated', 'using', 'linear', 'and', 'log', '-', 'binomial', 'regression', 'models', 'controlling', 'for', 'confounding', 'using', 'inverse', 'probability', 'of', 'treatment', 'weights', '(', 'IPTW', ')', 'truncated', 'at', 'the', '1st', 'and', '99th', 'percentiles', '.'],
+ 'pos_tags': [8, 13, 0, 8, 8, 13, 12, 13, 5, 0, 12, 8, 3, 16, 16, 0, 5, 0, 13, 0, 8, 8, 16, 1, 8, 16, 0, 8, 1, 8, 8, 13, 12, 13, 16, 1, 6, 0, 5, 0, 8, 13],
+ 'ner_tags': [0, 0, 0, 3, 4, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]
+}
+
+### Data Fields
+
+- id: the row identifier for the dataset point.
+- tokens: The tokens contained in the text.
+- pos_tags: the Part-of-Speech tags obtained for the corresponding token above from Spacy NER.
+- ner_tags: The tags for abbreviations and long-forms.
+
+
+### Data Splits
+
+|            | Train   | Valid | Test |
+| -----      | ------ | -----  | ---- |
+| Filtered   | 112652 |  24140 | 24140|
+| Unfiltered | 113860 |  24399 | 24399|
+
+
+## Dataset Creation
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+Extracting the data from PLOS Journals online and then tokenization, normalization.
+
+#### Who are the source language producers?
+
+PLOS Journal
+
+## Additional Information
+
+### Dataset Curators
+
+The dataset was initially created by Leonardo Zilio, Hadeel Saadany, Prashant Sharma,
+Diptesh Kanojia, Constantin Orasan.
+
+### Licensing Information
+
+CC-BY-SA 4.0
+
+### Citation Information
+
+[Needs More Information]
+
 ### Installation
 
 We use the custom NER pipeline in the [spaCy transformers](https://spacy.io/universe/project/spacy-transformers) library to train our models. This library supports training via any pre-trained language models available at the :rocket: [HuggingFace repository](https://huggingface.co/).<br/>