Update README.md

README.md

@@ -9,51 +9,28 @@ task_categories: question-generation
 task_ids: question-generation
 ---
 
-# Dataset Card for "qg_korquad"
-
-## Table of Contents
-- [Dataset Description](#dataset-description)
-  - [Dataset Summary](#dataset-summary)
-  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
-  - [Languages](#languages)
-- [Dataset Structure](#dataset-structure)
-  - [Data Instances](#data-instances)
-  - [Data Fields](#data-fields)
-  - [Data Splits](#data-splits)
-- [Dataset Creation](#dataset-creation)
-  - [Curation Rationale](#curation-rationale)
-  - [Source Data](#source-data)
-  - [Annotations](#annotations)
-  - [Personal and Sensitive Information](#personal-and-sensitive-information)
-- [Considerations for Using the Data](#considerations-for-using-the-data)
-  - [Social Impact of Dataset](#social-impact-of-dataset)
-  - [Discussion of Biases](#discussion-of-biases)
-  - [Other Known Limitations](#other-known-limitations)
-- [Additional Information](#additional-information)
-  - [Dataset Curators](#dataset-curators)
-  - [Licensing Information](#licensing-information)
-  - [Citation Information](#citation-information)
+# Dataset Card for "lmqg/qg_korquad"
 
 ## Dataset Description
 - **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation)
-- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+- **Paper:** [TBA](TBA)
 - **Point of Contact:** [Asahi Ushio](http://asahiushio.com/)
 
 ### Dataset Summary
-Modified version of [KorQuAD](https://huggingface.co/datasets/squad_kor_v1) for question generation (QG) task.
+This is a subset of [QG-Bench](https://github.com/asahi417/lm-question-generation/blob/master/QG_BENCH.md#datasets), a unified question generation benchmark proposed in
+ ["Generative Language Models for Paragraph-Level Question Generation: A Unified Benchmark and Evaluation, EMNLP 2022 main conference"](paper_link).
+This is a modified version of [KorQuAD](https://huggingface.co/datasets/squad_kor_v1) for question generation (QG) task.
 Since the original dataset only contains training/validation set, we manually sample test set from training set, which
 has no overlap in terms of the paragraph with the training set.
 
 ### Supported Tasks and Leaderboards
-* `question-generation`: The dataset can be used to train a model for question generation.
-  Success on this task is typically measured by achieving a high BLEU4/METEOR/ROUGE-L score.
-
+* `question-generation`: The dataset is assumed to be used to train a model for question generation.
+  Success on this task is typically measured by achieving a high BLEU4/METEOR/ROUGE-L/BERTScore/MoverScore (see our paper for more in detail).
+  
 ### Languages
 Korean (ko)
 
 ## Dataset Structure
-### Data Instances
-#### plain_text
 An example of 'train' looks as follows.
 ```
 {
@@ -66,9 +43,8 @@ An example of 'train' looks as follows.
   "sentence_answer": "함수해석학은 <hl> 함수의 공간(특히 무한차원)의 탐구 <hl> 에 주목한다."
 }
 ```
-### Data Fields
+
 The data fields are the same among all splits.
-#### plain_text
 - `question`: a `string` feature. 
 - `paragraph`: a `string` feature.
 - `answer`: a `string` feature.
@@ -81,38 +57,25 @@ Each of `paragraph_answer`, `paragraph_sentence`, and `sentence_answer` feature
 but with different information. The `paragraph_answer` and `sentence_answer` features are for answer-aware question generation and 
 `paragraph_sentence` feature is for sentence-aware question generation.
 
-### Data Splits
+## Data Splits
+
+|train|validation|test |
+|----:|---------:|----:|
+|54556|     5766 |5766 |
 
-|   name   |train|validation|test |
-|----------|----:|---------:|----:|
-|plain_text|54556|     5766 |5766 |
 
-## Dataset Creation
-### Curation Rationale
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-### Source Data
-#### Initial Data Collection and Normalization
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-#### Who are the source language producers?
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-### Annotations
-#### Annotation process
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-#### Who are the annotators?
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-### Personal and Sensitive Information
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-## Considerations for Using the Data
-### Social Impact of Dataset
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-### Discussion of Biases
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-### Other Known Limitations
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-## Additional Information
-### Dataset Curators
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-### Licensing Information
-Please refer the Licensing Information of the original dataset [here](https://huggingface.co/datasets/squad_kor_v1#licensing-information).
-### Citation Information
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+## Citation Information
+
+```
+@inproceedings{ushio-etal-2022-generative,
+    title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration: {A} {U}nified {B}enchmark and {E}valuation",
+    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",
+}
+```