remove

dataset_infos.json

@@ -1 +0,0 @@
-{"plain_text": {"description": "The FairytaleQA dataset focusing on narrative comprehension of kindergarten to eighth-grade students. Generated by educational experts based on an evidence-based theoretical framework, FairytaleQA consists of 10,580 explicit and implicit questions derived from 278 children-friendly stories, covering seven types of narrative elements or relations. This is for the Question Generation Task of FairytaleQA.\n", "citation": "@inproceedings{xu2022fairytaleqa,\n    author={Xu, Ying and Wang, Dakuo and Yu, Mo and Ritchie, Daniel and Yao, Bingsheng and Wu, Tongshuang and Zhang, Zheng and Li, Toby Jia-Jun and Bradford, Nora and Sun, Branda and Hoang, Tran Bao and Sang, Yisi and Hou, Yufang and Ma, Xiaojuan and Yang, Diyi and Peng, Nanyun and Yu, Zhou and Warschauer, Mark},\n    title = {Fantastic Questions and Where to Find Them: Fairytale{QA} -- An Authentic Dataset for Narrative Comprehension},\n    publisher = {Association for Computational Linguistics},\n    year = {2022}\n}\n", "homepage": "https://github.com/uci-soe/FairytaleQAData", "license": "", "features": {"story_name": {"dtype": "string", "id": null, "_type": "Value"}, "content": {"dtype": "string", "id": null, "_type": "Value"}, "answer": {"dtype": "string", "id": null, "_type": "Value"}, "gem_id": {"dtype": "string", "id": null, "_type": "Value"}, "target": {"dtype": "string", "id": null, "_type": "Value"}, "references": [{"dtype": "string", "id": null, "_type": "Value"}], "local_or_sum": {"dtype": "string", "id": null, "_type": "Value"}, "attribute": {"dtype": "string", "id": null, "_type": "Value"}, "ex_or_im": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "fairytale_qa", "config_name": "plain_text", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 11133353, "num_examples": 8548, "dataset_name": "fairytale_qa"}, "validation": {"name": "validation", "num_bytes": 1266866, "num_examples": 1025, "dataset_name": "fairytale_qa"}, "test": {"name": "test", "num_bytes": 1230365, "num_examples": 1007, "dataset_name": "fairytale_qa"}}, "download_checksums": {"train.json": {"num_bytes": 11159226, "checksum": "ef0235f3fa7560d04c46e1e5c174d601adff837641b209e4cafd605b5f60a2be"}, "valid.json": {"num_bytes": 1261009, "checksum": "213ba90343b3ef2fb01f4ecb16f68d7bd9ee048deec5338b4ac5888a072abb66"}, "test.json": {"num_bytes": 1232713, "checksum": "7e17ae3b8e417d0eb9962be564c4f6619ac510bf066b6c94c8e6c12b0ce97ff5"}}, "download_size": 13652948, "post_processing_size": null, "dataset_size": 13630584, "size_in_bytes": 27283532}}

fairytaleqa.py

@@ -74,14 +74,14 @@ _URLS = {
     "test": "test.json"
 }
 
-class FairytaleQAConfig(datasets.BuilderConfig):
+# class FairytaleQAConfig(datasets.BuilderConfig):
 
-    def __init__(self, **kwargs):
-        """
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(FairytaleQAConfig, self).__init__(**kwargs)
+#     def __init__(self, **kwargs):
+#         """
+#         Args:
+#           **kwargs: keyword arguments forwarded to super.
+#         """
+#         super(FairytaleQAConfig, self).__init__(**kwargs)
 
 # _URLS = "https://huggingface.co/datasets/GEM/FairytaleQA/resolve/main/fairytaleqa.zip"
 
@@ -103,12 +103,14 @@ class FairytaleQA(datasets.GeneratorBasedBuilder):
     # data = datasets.load_dataset('my_dataset', 'first_domain')
     # data = datasets.load_dataset('my_dataset', 'second_domain')
 
+    VERSION = datasets.Version("1.0.0")
+    DEFAULT_CONFIG_NAME = "fairytaleqa"
 
-    BUILDER_CONFIGS = [
-        FairytaleQAConfig(
-            name="plain_text", 
-            description="Plain Text")
-    ]
+    # BUILDER_CONFIGS = [
+    #     FairytaleQAConfig(
+    #         name="plain_text", 
+    #         description="Plain Text")
+    # ]
 
     # DEFAULT_CONFIG_NAME = "train"  # It's not mandatory to have a default configuration. Just use one if it make sense.
 
@@ -170,7 +172,7 @@ class FairytaleQA(datasets.GeneratorBasedBuilder):
         ]
 
     # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
-    def _generate_examples(self, filepath, split):
+    def _generate_examples(self, filepath, split, filepaths=None, lang=None):
         # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
         # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
         logger.info("generating examples from = %s", filepath)
@@ -186,7 +188,7 @@ class FairytaleQA(datasets.GeneratorBasedBuilder):
                     "answer": data['answer'],
                     "gem_id": f"GEM-FairytaleQA-{split}-{id_}",
                     "target": data['question'],
-                    "references": [ data['question'] ],
+                    "references": [] if split == "train" else [ data['question'] ],
                     "local_or_sum": data['local_or_sum'],
                     "attribute": data['attribute'],
                     "ex_or_im": data['ex_or_im']

test.json

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:7e17ae3b8e417d0eb9962be564c4f6619ac510bf066b6c94c8e6c12b0ce97ff5
-size 1232713

train.json

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:ef0235f3fa7560d04c46e1e5c174d601adff837641b209e4cafd605b5f60a2be
-size 11159226

valid.json

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:213ba90343b3ef2fb01f4ecb16f68d7bd9ee048deec5338b4ac5888a072abb66
-size 1261009