Update README.md

README.md

@@ -1,3 +1,97 @@
----
-license: mit
----
+---
+annotations_creators:
+- crowdsourced
+language:
+- en
+- ar
+- bn
+- fi
+- ja
+- ko
+- ru
+- te
+language_creators:
+- crowdsourced
+license:
+- mit
+multilinguality:
+- multilingual
+pretty_name: XORQA Reading Comprehension
+size_categories:
+- '10K<n<100K'
+source_datasets:
+- extended|wikipedia
+task_categories:
+- question-answering
+task_ids:
+- extractive-qa
+---
+
+# Dataset Card for "tydi_xor_rc_yes_no_unanswerable"
+
+
+## Dataset Description
+
+- **Homepage:** [https://github.com/google-research-datasets/tydiqa](https://github.com/google-research-datasets/tydiqa)
+- **Paper:** [Paper](https://aclanthology.org/2021.naacl-main.46)
+
+### Dataset Summary
+
+[TyDi QA](https://huggingface.co/datasets/tydiqa) is a question answering dataset covering 11 typologically diverse languages. 
+[XORQA](https://github.com/AkariAsai/XORQA) is an extension of the original TyDi QA dataset to also include unanswerable questions, where context documents are only in English but questions are in 7 languages.
+This dataset is a simplified version of the [Reading Comprehension data](https://nlp.cs.washington.edu/xorqa/XORQA_site/data/tydi_xor_rc_yes_no_unanswerable.zip) from XORQA.
+
+## Dataset Structure
+
+The dataset contains a train and a validation set, with 15445 and 3646 examples, respectively. Access them with
+
+```py
+from datasets import load_dataset
+dataset = load_dataset("coastalcph/tydi_xor_rc_yes_no_unanswerable")
+train_set = dataset["train"]
+validation_set = dataset["validation"]
+```
+
+### Data Instances
+
+Description of the dataset columns:
+
+| Column name                  | type        |  Description                                                                                                     |
+| -----------                  | ----------- | -----------                                                                                                      |
+| lang                     | str         | The language of the data instance                                                                                |
+| question                | str         | The question to answer                                                                                           |
+| context           | str         | The context, a Wikipedia paragraph that might or might not contain the answer to the question                    | 
+| is_impossible | bool | FALSE if the question can be answered given the context, TRUE otherwise |
+| answer_start  | int   | The character index in 'context' where the answer starts. If the question is unanswerable, this is -1  |
+| answer   | str   | The answer, a span of text from 'context'. If the question is unanswerable given the context, this can be 'yes' or 'no'            |
+
+
+## Useful stuff
+
+Check out the [datasets ducumentations](https://huggingface.co/docs/datasets/quickstart) to learn how to manipulate and use the dataset. Specifically, you might find the following functions useful:
+
+`dataset.filter`, for filtering out data (useful for keeping instances of specific languages, for example).
+
+`dataset.map`, for manipulating the dataset.
+
+`dataset.to_pandas`, to convert the dataset into a pandas.DataFrame format.
+
+
+```
+@inproceedings{xorqa,
+    title   = {{XOR} {QA}: Cross-lingual Open-Retrieval Question Answering},
+    author  = {Akari Asai and Jungo Kasai and Jonathan H. Clark and Kenton Lee and Eunsol Choi and Hannaneh Hajishirzi},
+    booktitle={NAACL-HLT},
+    year    = {2021}
+}
+```
+
+```
+@article{tydiqa,
+title   = {TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages},
+author  = {Jonathan H. Clark and Eunsol Choi and Michael Collins and Dan Garrette and Tom Kwiatkowski and Vitaly Nikolaev and Jennimaria Palomaki}
+year    = {2020},
+journal = {Transactions of the Association for Computational Linguistics}
+}
+
+```