Convert dataset to Parquet (#6)

- Convert dataset to Parquet (fe721a2c92746e3082b43f6cc968636cc1bd198c)
- Add 'masked_medhop' config data files (83a39d6809957620f77a744d34fb36e38566ba4d)
- Add 'wikihop' config data files (95ff35c439fdd18848475cb8fec18d157aa2848c)
- Add 'masked_wikihop' config data files (b04c4143c89a15596c43cbbb2fe05f2c6defc626)
- Delete loading script (7276113ed572d98b650ec397771f3fe1d8af63c4)
- Delete data file (f2879469fdc15902ef29a34dc8c8cf7af239d5a3)

README.md

@@ -1,10 +1,9 @@
 ---
 language:
 - en
-paperswithcode_id: null
 pretty_name: qangaroo
 dataset_info:
-- config_name: medhop
+- config_name: masked_medhop
   features:
   - name: query
     dtype: string
@@ -18,14 +17,14 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 93947725
+    num_bytes: 95813556
     num_examples: 1620
   - name: validation
-    num_bytes: 16463555
+    num_bytes: 16800542
     num_examples: 342
-  download_size: 339843061
-  dataset_size: 110411280
-- config_name: masked_medhop
+  download_size: 58801723
+  dataset_size: 112614098
+- config_name: masked_wikihop
   features:
   - name: query
     dtype: string
@@ -39,14 +38,14 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 95823986
-    num_examples: 1620
+    num_bytes: 348073986
+    num_examples: 43738
   - name: validation
-    num_bytes: 16802484
-    num_examples: 342
-  download_size: 339843061
-  dataset_size: 112626470
-- config_name: wikihop
+    num_bytes: 43663600
+    num_examples: 5129
+  download_size: 211302995
+  dataset_size: 391737586
+- config_name: medhop
   features:
   - name: query
     dtype: string
@@ -60,14 +59,14 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 325994029
-    num_examples: 43738
+    num_bytes: 93937294
+    num_examples: 1620
   - name: validation
-    num_bytes: 40869634
-    num_examples: 5129
-  download_size: 339843061
-  dataset_size: 366863663
-- config_name: masked_wikihop
+    num_bytes: 16461612
+    num_examples: 342
+  download_size: 57837760
+  dataset_size: 110398906
+- config_name: wikihop
   features:
   - name: query
     dtype: string
@@ -81,13 +80,38 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 348290479
+    num_bytes: 325777822
     num_examples: 43738
   - name: validation
-    num_bytes: 43689810
+    num_bytes: 40843303
     num_examples: 5129
-  download_size: 339843061
-  dataset_size: 391980289
+  download_size: 202454962
+  dataset_size: 366621125
+configs:
+- config_name: masked_medhop
+  data_files:
+  - split: train
+    path: masked_medhop/train-*
+  - split: validation
+    path: masked_medhop/validation-*
+- config_name: masked_wikihop
+  data_files:
+  - split: train
+    path: masked_wikihop/train-*
+  - split: validation
+    path: masked_wikihop/validation-*
+- config_name: medhop
+  data_files:
+  - split: train
+    path: medhop/train-*
+  - split: validation
+    path: medhop/validation-*
+- config_name: wikihop
+  data_files:
+  - split: train
+    path: wikihop/train-*
+  - split: validation
+    path: wikihop/validation-*
 ---
 
 # Dataset Card for "qangaroo"

qangaroo_v1.1.zip → masked_medhop/train-00000-of-00001.parquet

@@ -1,3 +1,3 @@
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-size 339843061
+oid sha256:88b2cb6463c9ba61430d4f2527b9f9dc07b1e94ea7fa783a3e95eef1045ded88
+size 50027308

masked_medhop/validation-00000-of-00001.parquet

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+size 8774415

masked_wikihop/train-00000-of-00001.parquet

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+size 187716381

masked_wikihop/validation-00000-of-00001.parquet

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+size 23586614

medhop/train-00000-of-00001.parquet

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+size 49190527

medhop/validation-00000-of-00001.parquet

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+oid sha256:1c8b0249a81eba3fd646c6589f56d56adb583e384967e8af969aca67e51e93d9
+size 8647233

qangaroo.py

@@ -1,126 +0,0 @@
-"""TODO(qangaroo): Add a description here."""
-
-
-import json
-import os
-
-import datasets
-
-
-# TODO(qangaroo): BibTeX citation
-
-_CITATION = """
-"""
-
-# TODO(quangaroo):
-_DESCRIPTION = """\
-  We have created two new Reading Comprehension datasets focussing on multi-hop (alias multi-step) inference.
-
-Several pieces of information often jointly imply another fact. In multi-hop inference, a new fact is derived by combining facts via a chain of multiple steps.
-
-Our aim is to build Reading Comprehension methods that perform multi-hop inference on text, where individual facts are spread out across different documents.
-
-The two QAngaroo datasets provide a training and evaluation resource for such methods.
-"""
-
-_MEDHOP_DESCRIPTION = """\
-  With the same format as WikiHop, this dataset is based on research paper abstracts from PubMed, and the queries are about interactions between pairs of drugs.
-  The correct answer has to be inferred by combining information from a chain of reactions of drugs and proteins.
-  """
-_WIKIHOP_DESCRIPTION = """\
-  With the same format as WikiHop, this dataset is based on research paper abstracts from PubMed, and the queries are about interactions between pairs of drugs.
-   The correct answer has to be inferred by combining information from a chain of reactions of drugs and proteins.
-  """
-
-_URL = "qangaroo_v1.1.zip"
-
-
-class QangarooConfig(datasets.BuilderConfig):
-    def __init__(self, data_dir, **kwargs):
-        """BuilderConfig for qangaroo dataset
-
-        Args:
-          data_dir: directory for the given dataset name
-          **kwargs: keyword arguments forwarded to super.
-
-        """
-
-        super(QangarooConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
-
-        self.data_dir = data_dir
-
-
-class Qangaroo(datasets.GeneratorBasedBuilder):
-    """TODO(qangaroo): Short description of my dataset."""
-
-    # TODO(qangaroo): Set up version.
-    VERSION = datasets.Version("0.1.0")
-    BUILDER_CONFIGS = [
-        QangarooConfig(name="medhop", description=_MEDHOP_DESCRIPTION, data_dir="medhop"),
-        QangarooConfig(name="masked_medhop", description=_MEDHOP_DESCRIPTION, data_dir="medhop"),
-        QangarooConfig(name="wikihop", description=_WIKIHOP_DESCRIPTION, data_dir="wikihop"),
-        QangarooConfig(name="masked_wikihop", description=_WIKIHOP_DESCRIPTION, data_dir="wikihop"),
-    ]
-
-    def _info(self):
-        # TODO(qangaroo): 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(
-                {
-                    # These are the features of your dataset like images, labels ...
-                    "query": datasets.Value("string"),
-                    "supports": datasets.features.Sequence(datasets.Value("string")),
-                    "candidates": datasets.features.Sequence(datasets.Value("string")),
-                    "answer": datasets.Value("string"),
-                    "id": datasets.Value("string")
-                    # 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="http://qangaroo.cs.ucl.ac.uk/index.html",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        # TODO(qangaroo): 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(_URL)
-        data_dir = os.path.join(dl_dir, "qangaroo_v1.1")
-        train_file = "train.masked.json" if "masked" in self.config.name else "train.json"
-        dev_file = "dev.masked.json" if "masked" in self.config.name else "dev.json"
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": os.path.join(data_dir, self.config.data_dir, train_file)},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": os.path.join(data_dir, self.config.data_dir, dev_file)},
-            ),
-        ]
-
-    def _generate_examples(self, filepath):
-        """Yields examples."""
-        # TODO(quangaroo): Yields (key, example) tuples from the dataset
-        with open(filepath, encoding="utf-8") as f:
-            data = json.load(f)
-            for example in data:
-                id_ = example["id"]
-                yield id_, {
-                    "id": example["id"],
-                    "query": example["query"],
-                    "supports": example["supports"],
-                    "candidates": example["candidates"],
-                    "answer": example["answer"],
-                }

wikihop/train-00000-of-00001.parquet

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+size 179876427

wikihop/validation-00000-of-00001.parquet

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+size 22578535