Convert dataset to Parquet

README.md

@@ -23,6 +23,7 @@ pretty_name: Abductive Reasoning in narrative Text
 tags:
 - abductive-natural-language-inference
 dataset_info:
+  config_name: anli
   features:
   - name: observation_1
     dtype: string
@@ -39,16 +40,23 @@ dataset_info:
           '0': '0'
           '1': '1'
           '2': '2'
-  config_name: anli
   splits:
   - name: validation
-    num_bytes: 312314
+    num_bytes: 311146
     num_examples: 1532
   - name: train
-    num_bytes: 34046304
+    num_bytes: 33918790
     num_examples: 169654
-  download_size: 5118294
-  dataset_size: 34358618
+  download_size: 9191805
+  dataset_size: 34229936
+configs:
+- config_name: anli
+  data_files:
+  - split: validation
+    path: anli/validation-*
+  - split: train
+    path: anli/train-*
+  default: true
 ---
 
 # Dataset Card for "art"

anli/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5ed3125b054c0918b77e84e5babb0cc41d3636093b7ba66e135017a564c129c8
+size 8983169

anli/validation-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:466c1f53fe13a20101d612a5b7d837ec5b5101bf7a0f8c64e32ea0277b754f61
+size 208636

art.py

@@ -1,116 +0,0 @@
-"""TODO(art): Add a description here."""
-
-
-import json
-import os
-
-import datasets
-
-
-# TODO(art): BibTeX citation
-_CITATION = """\
-@InProceedings{anli,
-  author = {Chandra, Bhagavatula and Ronan, Le Bras and Chaitanya, Malaviya and Keisuke, Sakaguchi and Ari, Holtzman
-    and Hannah, Rashkin and Doug, Downey and Scott, Wen-tau Yih and Yejin, Choi},
-  title = {Abductive Commonsense Reasoning},
-  year = {2020}
-}"""
-
-# TODO(art):
-_DESCRIPTION = """\
-the Abductive Natural Language Inference Dataset from AI2
-"""
-_DATA_URL = "https://storage.googleapis.com/ai2-mosaic/public/alphanli/alphanli-train-dev.zip"
-
-
-class ArtConfig(datasets.BuilderConfig):
-    """BuilderConfig for Art."""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig for Art.
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(ArtConfig, self).__init__(version=datasets.Version("0.1.0", ""), **kwargs)
-
-
-class Art(datasets.GeneratorBasedBuilder):
-    """TODO(art): Short description of my dataset."""
-
-    # TODO(art): Set up version.
-    VERSION = datasets.Version("0.1.0")
-    BUILDER_CONFIGS = [
-        ArtConfig(
-            name="anli",
-            description="""\
-          the Abductive Natural Language Inference Dataset from AI2.
-          """,
-        ),
-    ]
-
-    def _info(self):
-        # TODO(art): Specifies the datasets.DatasetInfo object
-        return datasets.DatasetInfo(
-            # This is the description that will appear on the datasets page.
-            description=_DESCRIPTION,
-            # datasets.features.FeatureConnectors
-            features=datasets.Features(
-                {
-                    "observation_1": datasets.Value("string"),
-                    "observation_2": datasets.Value("string"),
-                    "hypothesis_1": datasets.Value("string"),
-                    "hypothesis_2": datasets.Value("string"),
-                    "label": datasets.features.ClassLabel(num_classes=3)
-                    # These are the features of your dataset like images, labels ...
-                }
-            ),
-            # 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="https://leaderboard.allenai.org/anli/submissions/get-started",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        # TODO(art): Downloads the data and defines the splits
-        # dl_manager is a datasets.download.DownloadManager that can be used to
-        # download and extract URLs
-        dl_dir = dl_manager.download_and_extract(_DATA_URL)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "filepath": os.path.join(dl_dir, "dev.jsonl"),
-                    "labelpath": os.path.join(dl_dir, "dev-labels.lst"),
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "filepath": os.path.join(dl_dir, "train.jsonl"),
-                    "labelpath": os.path.join(dl_dir, "train-labels.lst"),
-                },
-            ),
-        ]
-
-    def _generate_examples(self, filepath, labelpath):
-        """Yields examples."""
-        # TODO(art): Yields (key, example) tuples from the dataset
-        data = []
-        for line in open(filepath, encoding="utf-8"):
-            data.append(json.loads(line))
-        labels = []
-        with open(labelpath, encoding="utf-8") as f:
-            for word in f:
-                labels.append(word)
-        for idx, row in enumerate(data):
-            yield idx, {
-                "observation_1": row["obs1"],
-                "observation_2": row["obs2"],
-                "hypothesis_1": row["hyp1"],
-                "hypothesis_2": row["hyp2"],
-                "label": labels[idx],
-            }

dataset_infos.json

@@ -1 +0,0 @@
-{"anli": {"description": "the Abductive Natural Language Inference Dataset from AI2\n", "citation": "@InProceedings{anli,\n  author = \"Chandra, Bhagavatula\n    and Ronan, Le Bras\n    and Chaitanya, Malaviya\n    and Keisuke, Sakaguchi\n    and Ari, Holtzman\n    and Hannah, Rashkin\n    and Doug, Downey\n    and Scott, Wen-tau Yih\n    and Yejin, Choi\",\n  title = \"Abductive Commonsense Reasoning\",\n  year = \"2020\",\n}", "homepage": "https://leaderboard.allenai.org/anli/submissions/get-started", "license": "", "features": {"observation_1": {"dtype": "string", "id": null, "_type": "Value"}, "observation_2": {"dtype": "string", "id": null, "_type": "Value"}, "hypothesis_1": {"dtype": "string", "id": null, "_type": "Value"}, "hypothesis_2": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 3, "names": ["0", "1", "2"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "supervised_keys": null, "builder_name": "art", "config_name": "anli", "version": {"version_str": "0.1.0", "description": "", "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 34046304, "num_examples": 169654, "dataset_name": "art"}, "validation": {"name": "validation", "num_bytes": 312314, "num_examples": 1532, "dataset_name": "art"}}, "download_checksums": {"https://storage.googleapis.com/ai2-mosaic/public/alphanli/alphanli-train-dev.zip": {"num_bytes": 5118294, "checksum": "24840b27553e93ec625ae020dbf78d92daeae4be31ebbd469a0c9f6f99ed1c8d"}}, "download_size": 5118294, "dataset_size": 34358618, "size_in_bytes": 39476912}}