Update README.md

README.md

@@ -34,6 +34,13 @@ configs:
     path: data/validation-*
   - split: test
     path: data/test-*
+license: cc0-1.0
+task_categories:
+- question-answering
+language:
+- nb
+size_categories:
+- 1K<n<10K
 ---
 
 # Dataset Card for Dataset Name
@@ -74,7 +81,34 @@ The dataset is intended to be used for NLP model development and benchmarking.
 
 <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
 
-[More Information Needed]
+**Data Instances**
+
+```
+{
+    "id": "1",
+    "context": "This is a test context",
+    "question": "This is a question",
+    "answers": {
+        "answer_start": [1],
+        "text": ["This is an answer"]
+    },
+}
+```
+
+**Data Fields**
+
+```
+  id: 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.
+```
+
+**Dataset Splits**
+
+NorQuAD consists of training (3808 examples), validation (472), and public test (472) sets.
 
 ## Dataset Creation
 
@@ -135,15 +169,15 @@ The annotators were provided with a set of initial instructions, largely based o
 dataset (Rajpurkar et al., 2016) and the GermanQuAD data (Moller et al., 2021). These instructions were subsequently refined following regular
 meetings with the annotation team.
 The annotation guidelines provided to the annotators are available (here)[https://github.com/ltgoslo/NorQuAD/blob/main/guidelines.md].
-For annotation, we used the Haystack annotation tool which was designed for QA collection.
+For annotation, we used the Haystack annotation tool, which was designed for QA collection.
 
 
 #### Human validation
 
-In a separate stage, the annotators validated a subset of the NorQuAD dataset. In this phase each
+In a separate stage, the annotators validated a subset of the NorQuAD dataset. In this phase, each
 annotator replied to the questions created by the
 other annotator. We chose the question-answer
-pairs for validation at random. In total, 1378 questions from the set of question-answer pairs, were
+pairs for validation at random. In total, 1378 questions from the set of question-answer pairs were
 answered by validators.
 
 
@@ -154,7 +188,7 @@ answered by validators.
 
 Two students of the Master’s program in Natural Language Processing at the University of Oslo,
 both native Norwegian speakers, created question-answer pairs from the collected passages. Each
-student received separate set of passages for annotation. The students received financial remuneration for their efforts and are co-authors of the
+student received a separate set of passages for annotation. The students received financial remuneration for their efforts and are co-authors of the
 paper describing the resource. 
 
 
@@ -164,7 +198,7 @@ paper describing the resource.
 <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
 
 **BibTeX:**
-
+```
 @inproceedings{
 ivanova2023norquad,
 title={NorQu{AD}: Norwegian Question Answering Dataset},
@@ -173,6 +207,7 @@ booktitle={The 24th Nordic Conference on Computational Linguistics},
 year={2023},
 url={https://aclanthology.org/2023.nodalida-1.17.pdf}
 }
+```
 **APA:**
 
 [More Information Needed]
@@ -184,4 +219,4 @@ Vladislav Mikhailov and Lilja Øvrelid
 
 ## Dataset Card Contact
 
-[email protected] and [email protected]
+[email protected] and [email protected]