challenge sets

animal.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:89987c9d9dc4babbcdac10bea176cc5fa83dad5e37115a97c2864d6bf534c3e8
-size 490633812
+oid sha256:dd99a2a62e77cb291972bd5b51097c4619ce37ca86dab28a2cd6cb63cfc8198e
+size 493575209

company.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:db1dfb103d15dc3da33c47aedcd9b4f73f95a2f1186654fbbc3ac8d36cec6504
-size 868626354
+oid sha256:9856c544319077b62bbb6c940daa7a9e53b179cee7bb84f5d731f65735e22e33
+size 872354086

film.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c50bcf4978f20ffa898e4e99820d8ad2a5399f63ef94870eaada71161fe93d3e
-size 855752717
+oid sha256:62ca469c0a6bb5e01dbbff8a1f7e34a45b7b827ffc5dd358b10e42ebf6980a37
+size 859086412

wiki_cat_sum.py

@@ -37,14 +37,14 @@ _CITATION = """\
 # TODO: Add description of the dataset here
 # You can copy an official description
 _DESCRIPTION = """\
-This new dataset is designed to solve this great NLP task and is crafted with a lot of care.
+Summarise the most important facts of a given entity in the Film, Company, and Animal domains from a cluster of related documents.
 """
 
 # TODO: Add a link to an official homepage for the dataset here
 _HOMEPAGE = "https://datashare.ed.ac.uk/handle/10283/3368"
 
 # TODO: Add the licence for the dataset here if you can find it
-_LICENSE = ""
+_LICENSE = "CC BY-SA 3.0"
 
 # TODO: Add link to the official dataset URLs here
 # The HuggingFace dataset library don't host the datasets but only point to the original files
@@ -63,9 +63,6 @@ class WikiCatSum(datasets.GeneratorBasedBuilder):
 
     VERSION = datasets.Version("0.1.0")
 
-    # 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
@@ -125,6 +122,12 @@ class WikiCatSum(datasets.GeneratorBasedBuilder):
         # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
         my_urls = _URLs[self.config.name]
         data_dir = dl_manager.download_and_extract(my_urls)
+        challenge_sets = [
+            ("challenge_%s_nov_%s" % (split,lvl),"%s-%s_nv2_%s.jsonl" % (split,self.config.name,lvl)) \
+                for split in ["train","valid","test"] for lvl in ["low","mid","high"]
+        ]
+        # + ...
+
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
@@ -150,7 +153,16 @@ class WikiCatSum(datasets.GeneratorBasedBuilder):
                     "split": "dev",
                 },
             ),
-        ]
+        ] + [
+                datasets.SplitGenerator(
+                    name=challenge_split,
+                    gen_kwargs={
+                        "filepath": os.path.join(data_dir, filename),
+                        "split": challenge_split,
+                    },
+                )
+                for challenge_split, filename in challenge_sets
+            ]
 
     def _generate_examples(
         self, filepath, split  # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`