Update README.md

README.md

@@ -13,12 +13,12 @@ tags:
 - question-generation
 ---
 
-# Dataset Card for "lmqg/qag_tweetqa"
+# Dataset Card for "lmqg/qg_tweetqa"
 
 
 ## Dataset Description
 - **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation)
-- **Paper:** [TBA](TBA)
+- **Paper:** [https://arxiv.org/abs/2210.03992](https://arxiv.org/abs/2210.03992)
 - **Point of Contact:** [Asahi Ushio](http://asahiushio.com/)
 
 ### Dataset Summary
@@ -35,27 +35,37 @@ English (en)
 An example of 'train' looks as follows.
 ```
 {
-  "paragraph": "I would hope that Phylicia Rashad would apologize now that @missjillscott has! You cannot discount 30 victims who come with similar stories.— JDWhitner (@JDWhitner) July 7, 2015",
-  "questions": [ "what should phylicia rashad do now?", "how many victims have come forward?" ],
-  "answers": [ "apologize", "30" ],
-  "questions_answers": "Q: what should phylicia rashad do now?, A: apologize Q: how many victims have come forward?, A: 30"
+  'answer': 'vine',
+  'paragraph_question': 'question: what site does the link take you to?, context:5 years in 5 seconds. Darren Booth (@darbooth) January 25, 2013',
+  'question': 'what site does the link take you to?',
+  'paragraph': '5 years in 5 seconds. Darren Booth (@darbooth) January 25, 2013'
 }
 ```
 The data fields are the same among all splits.
 - `questions`: a `list` of `string` features. 
 - `answers`: a `list` of `string` features.
 - `paragraph`: a `string` feature.
-- `questions_answers`: a `string` feature.
+- `question_answer`: a `string` feature.
 
 ## Data Splits
 
 |train|validation|test |
 |----:|---------:|----:|
-|4536 |       583|  583|
+|9489 |      1086| 1203|
 
 
 ## Citation Information
 
 ```
-TBA
+@inproceedings{ushio-etal-2022-generative,
+    title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration",
+    author = "Ushio, Asahi  and
+        Alva-Manchego, Fernando  and
+        Camacho-Collados, Jose",
+    booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
+    month = dec,
+    year = "2022",
+    address = "Abu Dhabi, U.A.E.",
+    publisher = "Association for Computational Linguistics",
+}
 ```