Update metadata

README.md

@@ -482,7 +482,7 @@ config_names:
 
 ### Dataset Summary
 
-We introduce WikiLingua, a large-scale, multilingual dataset for the evaluation of crosslingual abstractive summarization systems. We extract article and summary pairs in 18 languages from WikiHow, a high quality, collaborative resource of how-to guides on a diverse set of topics written by human authors. We create gold-standard article-summary alignments across languages by aligning the images that are used to describe each how-to step in an article.
+We introduce WikiLingua, a large-scale, multilingual dataset for the evaluation of cross-lingual abstractive summarization systems. We extract article and summary pairs in 18 languages from WikiHow, a high quality, collaborative resource of how-to guides on a diverse set of topics written by human authors. We create gold-standard article-summary alignments across languages by aligning the images that are used to describe each how-to step in an article.
 
 ### Supported Tasks and Leaderboards
 
@@ -631,12 +631,20 @@ ______________________________
 ### Citation Information
 
 ```bibtex
-@article{ladhak-wiki-2020,
-  title   = {WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization},
-  authors = {Faisal Ladhak, Esin Durmus, Claire Cardie and Kathleen McKeown},
-  journal = {arXiv preprint arXiv:2010.03093},
-  year    = {2020},
-  url     = {https://arxiv.org/abs/2010.03093}
+@inproceedings{ladhak-etal-2020-wikilingua,
+    title = "{W}iki{L}ingua: A New Benchmark Dataset for Cross-Lingual Abstractive Summarization",
+    author = "Ladhak, Faisal  and
+      Durmus, Esin  and
+      Cardie, Claire  and
+      McKeown, Kathleen",
+    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2020",
+    month = nov,
+    year = "2020",
+    address = "Online",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2020.findings-emnlp.360",
+    doi = "10.18653/v1/2020.findings-emnlp.360",
+    pages = "4034--4048",
 }
 ```
 

wiki_lingua.py

@@ -12,7 +12,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-"""TODO: Add a description here."""
+"""WikiLingua."""
 
 
 import json
@@ -22,18 +22,26 @@ import datasets
 
 # Find for instance the citation on arxiv or on the dataset repo/website
 _CITATION = """\
-@article{ladhak-wiki-2020,
-  title   = {WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization},
-  authors = {Faisal Ladhak, Esin Durmus, Claire Cardie and Kathleen McKeown},
-  journal = {arXiv preprint arXiv:2010.03093},
-  year    = {2020},
-  url     = {https://arxiv.org/abs/2010.03093}
+@inproceedings{ladhak-etal-2020-wikilingua,
+    title = "{W}iki{L}ingua: A New Benchmark Dataset for Cross-Lingual Abstractive Summarization",
+    author = "Ladhak, Faisal  and
+      Durmus, Esin  and
+      Cardie, Claire  and
+      McKeown, Kathleen",
+    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2020",
+    month = nov,
+    year = "2020",
+    address = "Online",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2020.findings-emnlp.360",
+    doi = "10.18653/v1/2020.findings-emnlp.360",
+    pages = "4034--4048",
 }
 """
 
 _DESCRIPTION = """\
 WikiLingua is a large-scale multilingual dataset for the evaluation of
-crosslingual abstractive summarization systems. The dataset includes ~770k
+cross-lingual abstractive summarization systems. The dataset includes ~770k
 article and summary pairs in 18 languages from WikiHow. The gold-standard
 article-summary alignments across languages was done by aligning the images
 that are used to describe each how-to step in an article.
@@ -68,21 +76,10 @@ _LANGUAGES = [
 
 
 class WikiLingua(datasets.GeneratorBasedBuilder):
-    """TODO: Short description of my dataset."""
+    """WikiLingua dataset."""
 
     VERSION = datasets.Version("1.1.1")
 
-    # This is an example of a dataset with multiple configurations.
-    # If you don't want/need to define several sub-sets in your dataset,
-    # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
-
-    # If you need to make complex sub-parts in the datasets with configurable options
-    # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
-    # BUILDER_CONFIG_CLASS = MyBuilderConfig
-
-    # You will  be able to load one or the other configurations in the following list with
-    # data = datasets.load_dataset('my_dataset', 'first_domain')
-    # data = datasets.load_dataset('my_dataset', 'second_domain')
     BUILDER_CONFIGS = [
         datasets.BuilderConfig(
             name=lang,
@@ -129,10 +126,6 @@ class WikiLingua(datasets.GeneratorBasedBuilder):
             description=_DESCRIPTION,
             # This defines the different columns of the dataset and their types
             features=features,  # Here we define them above because they are different between the two configurations
-            # If there's a common (input, target) tuple from the features,
-            # specify them here. They'll be used if as_supervised=True in
-            # builder.as_dataset.
-            supervised_keys=None,
             # Homepage of the dataset for documentation
             homepage=_HOMEPAGE,
             # License for the dataset if available