Update readme

README.md

@@ -24,7 +24,7 @@ task_ids:
 - extractive-qa
 ---
 
-# Dataset Card for [Dataset Name]
+# Dataset Card for the Qur'anic Reading Comprehension Dataset (QRCD)
 
 ## Table of Contents
 - [Table of Contents](#table-of-contents)
@@ -64,22 +64,22 @@ task_ids:
 The QRCD (Qur'anic Reading Comprehension Dataset) is composed of 1,093 tuples of question-passage pairs that are 
   coupled with their extracted answers to constitute 1,337 question-passage-answer triplets.
 
-The distribution of the dataset into training, development and test sets is shown below.
-
-| **Dataset** | **%** | **# Question-Passage  Pairs** | **# Question-Passage-Answer  Triplets** |
-|-------------|:-----:|:-----------------------------:|:---------------------------------------:|
-| Training    |  65%  |              710              |                   861                   |
-| Development |  10%  |              109              |                   128                   |
-| Test        |  25%  |              274              |                   348                   |
-| All         | 100%  |             1,093             |                  1,337                  |
-
 ### Supported Tasks and Leaderboards
 
-[More Information Needed]
+This task is evaluated as a ranking task.
+To give credit to a QA system that may retrieve an answer (not necessarily at the first rank) that does not fully 
+  match one of the gold answers but partially matches it, we use partial Reciprocal Rank (pRR) measure.
+It is a variant of the traditional Reciprocal Rank evaluation metric that considers partial matching.
+pRR is the official evaluation measure of this shared task.
+We will also report Exact Match (EM) and F1@1, which are evaluation metrics applied only on the top predicted answer.
+The EM metric is a binary measure that rewards a system only if the top predicted answer exactly matches one of the 
+  gold answers.
+Whereas, the F1@1 metric measures the token overlap between the top predicted answer and the best matching gold answer.
+To get an overall evaluation score, each of the above measures is averaged over all questions.
 
 ### Languages
 
-* Arabic
+Qur'anic Arabic
 
 ## Dataset Structure
 
@@ -123,9 +123,12 @@ We have chosen the simple-clean text style of Tanzil version 1.0.2.
 
 ### Data Splits
 
-* Training  (65%)
-* Development (10%)
-* Test (25%)
+| **Dataset** | **%** | **# Question-Passage  Pairs** | **# Question-Passage-Answer  Triplets** |
+|-------------|:-----:|:-----------------------------:|:---------------------------------------:|
+| Training    |  65%  |              710              |                   861                   |
+| Development |  10%  |              109              |                   128                   |
+| Test        |  25%  |              274              |                   348                   |
+| All         | 100%  |             1,093             |                  1,337                  |
 
 ## Dataset Creation