changes

README.md

@@ -1,25 +1,11 @@
-<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>
-
-# PLOD: An Abbreviation Detection Dataset  
-
-This is the repository for PLOD Dataset submitted to LREC 2022. The dataset can help build sequence labelling models for the task Abbreviation Detection.
-
-### Dataset
-
-We provide two variants of our dataset - Filtered and Unfiltered. They are described in our paper here.
-
-1. The Filtered version can be accessed via [Huggingface Datasets here](https://huggingface.co/datasets/surrey-nlp/PLOD-filtered) and a [CONLL format is present here](https://github.com/surrey-nlp/PLOD-AbbreviationDetection).<br/>
-
-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/>
-
 annotations_creators:
-- other
+- Leonardo Zilio, Hadeel Saadany, Prashant Sharma, Diptesh Kanojia, Constantin Orasan 
 language_creators:
 - found
 languages:
 - en
 licenses:
-- cc-by-sa 4.0
+- cc-by-sa4.0
 multilinguality:
 - monolingual
 paperswithcode_id: acronym-identification
@@ -33,6 +19,18 @@ task_categories:
 task_ids:
 - named-entity-recognition
 
+# PLOD: An Abbreviation Detection Dataset  
+
+This is the repository for PLOD Dataset submitted to LREC 2022. The dataset can help build sequence labelling models for the task Abbreviation Detection.
+
+### Dataset
+
+We provide two variants of our dataset - Filtered and Unfiltered. They are described in our paper here.
+
+1. The Filtered version can be accessed via [Huggingface Datasets here](https://huggingface.co/datasets/surrey-nlp/PLOD-filtered) and a [CONLL format is present here](https://github.com/surrey-nlp/PLOD-AbbreviationDetection).<br/>
+
+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-filtered
 
 ## Table of Contents