Update README.md

README.md

@@ -10,7 +10,6 @@ multilinguality:
 - monolingual
 task_ids:
 - extractive-qa
-paperswithcode_id: nlquad-a-non-factoid-long-question-answering
 dataset_info:
   features:
   - name: title
@@ -64,8 +63,8 @@ dataset_info:
 
 ## Dataset Description
 
-- **Repository: [Github](https://github.com/ASoleimaniB/NLQuAD)**
-- **Paper:[NLQuAD: A Non-Factoid Long Question Answering Data Set](https://aclanthology.org/2021.eacl-main.106/)**
+- **Repository: [https://github.com/ASoleimaniB/NLQuAD](https://github.com/ASoleimaniB/NLQuAD)**
+- **Paper:[https://aclanthology.org/2021.eacl-main.106/](https://aclanthology.org/2021.eacl-main.106/)**
 
 ### Dataset Summary
 
@@ -85,16 +84,39 @@ We automatically extract target answers because annotating for non-factoid long
 #### plain_text
 An example of 'train' looks as follows.
 
-```
+```json
 {
-    "answers": {
-        "answer_start": [1],
-        "text": ["This is a test text"]
-    },
-    "context": "This is a test context.",
-    "id": "1",
-    "question": "Is this a test?",
-    "title": "train test"
+    "title": "Khashoggi murder: Body 'dissolved in acid'",
+    "date": "2 November 2018",
+    "paragraphs":[
+        {
+            "context": "A top Turkish official, presidential adviser Yasin Aktay, has said ....",
+            "qas":[
+              {
+                  "question":"What was said in the crown prince's alleged phone call?",
+                  "id":"0_0",
+                  "answers":[
+                    {
+                      "text":"During the call with President Donald Trump\'s son-in-law Jared Kushner and national ....",
+                      "answer_start":1352,
+                      "answer_end": 2108,
+                    }
+                  ]
+              },
+              {
+                  "question":'What has the investigation found so far?',
+                  "id":"0_1",
+                  "answers":[
+                    {
+                      "text":"There is still no consensus on how Khashoggi died. He entered ....",
+                      "answer_start":2109,
+                      "answer_end": 3128,
+                    }
+                  ]
+              },
+            ]
+        }
+    ]
 }
 ```
 
@@ -103,20 +125,23 @@ An example of 'train' looks as follows.
 The data fields are the same among all splits.
 
 #### plain_text
-- `id`: a `string` feature.
 - `title`: a `string` feature.
-- `context`: a `string` feature.
-- `question`: a `string` feature.
-- `answers`: a dictionary feature containing:
-  - `text`: a `string` feature.
-  - `answer_start`: a `int32` feature.
-
-
+- `date`: a `string` feature.
+- `paragraphs`: a list feature containing dictionaries:
+  - `context`: a `string` feature.
+  - `qas`: a list feature containing dictionaries:
+    - `question`: a `string` feature.
+    - `id`: a `string` feature.
+    - `answers`: a list feature containing dictionaries:
+      - `text`: a `string` feature.
+      - `answer_start`: a `int32` feature.
+      - `answer_end`: a `int32` feature
+      - 
 ### Data Splits
 
 |   name   |train|test|validation|
 |----------|----:|----:|---------:|
-|plain_text|87599|10570|     10570|
+|plain_text|10259| 1280|     1280|
 
 
 ## Additional Information
@@ -127,7 +152,8 @@ This dataset is distributed under the [CC BY-NC](https://creativecommons.org/lic
 
 ### Citation Information
 
-BibTeX:```json
+BibTeX:
+```json
 @inproceedings{soleimani-etal-2021-nlquad,
     title = "{NLQ}u{AD}: A Non-Factoid Long Question Answering Data Set",
     author = "Soleimani, Amir  and