Convert dataset to Parquet (#4)

- Convert dataset to Parquet (df640036109ffb1ef30763bbe7c5c8e4f5f72b98)
- Delete loading script (e90c21e8bdaa4868d95f261b5a3a70e09d17c6a3)

README.md

@@ -1,15 +1,14 @@
 ---
 annotations_creators:
 - crowdsourced
-language:
-- en
 language_creators:
 - found
+language:
+- en
 license:
 - cc-by-4.0
 multilinguality:
 - monolingual
-pretty_name: Coarse Discourse
 size_categories:
 - 100K<n<1M
 source_datasets:
@@ -19,6 +18,7 @@ task_categories:
 task_ids:
 - multi-class-classification
 paperswithcode_id: coarse-discourse
+pretty_name: Coarse Discourse
 dataset_info:
   features:
   - name: title
@@ -51,10 +51,15 @@ dataset_info:
       dtype: string
   splits:
   - name: train
-    num_bytes: 45443464
+    num_bytes: 45097556
     num_examples: 116357
-  download_size: 4636201
-  dataset_size: 45443464
+  download_size: 4256575
+  dataset_size: 45097556
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
 ---
 
 # Dataset Card for "coarse_discourse"

coarse_discourse.py

@@ -1,116 +0,0 @@
-"""TODO(coarse_discourse): Add a description here."""
-
-
-import json
-
-import datasets
-
-
-# TODO(coarse_discourse): BibTeX citation
-_CITATION = """\
-@inproceedings{coarsediscourse, title={Characterizing Online Discussion Using Coarse Discourse Sequences}, author={Zhang, Amy X. and Culbertson, Bryan and Paritosh, Praveen}, booktitle={Proceedings of the 11th International AAAI Conference on Weblogs and Social Media}, series={ICWSM '17}, year={2017}, location = {Montreal, Canada} }
-"""
-
-# TODO(coarse_discourse):
-_DESCRIPTION = """\
-dataset contains discourse annotation and relation on threads from reddit during 2016
-"""
-# From: https://github.com/google-research-datasets/coarse-discourse
-_URL = "https://raw.githubusercontent.com/google-research-datasets/coarse-discourse/master/coarse_discourse_dataset.json"
-
-
-class CoarseDiscourse(datasets.GeneratorBasedBuilder):
-    """TODO(coarse_discourse): Short description of my dataset."""
-
-    # TODO(coarse_discourse): Set up version.
-    VERSION = datasets.Version("0.1.0")
-
-    def _info(self):
-        # TODO(coarse_discourse): 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 ...
-                    "title": datasets.Value("string"),
-                    "is_self_post": datasets.Value("bool"),
-                    "subreddit": datasets.Value("string"),
-                    "url": datasets.Value("string"),
-                    "majority_link": datasets.Value("string"),
-                    "is_first_post": datasets.Value("bool"),
-                    "majority_type": datasets.Value("string"),
-                    "id_post": datasets.Value("string"),
-                    "post_depth": datasets.Value("int32"),
-                    "in_reply_to": datasets.Value("string"),
-                    "annotations": datasets.features.Sequence(
-                        {
-                            "annotator": datasets.Value("string"),
-                            "link_to_post": datasets.Value("string"),
-                            "main_type": datasets.Value("string"),
-                        }
-                    ),
-                }
-            ),
-            # 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://github.com/google-research-datasets/coarse-discourse",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        # TODO(coarse_discourse): Downloads the data and defines the splits
-        # dl_manager is a datasets.download.DownloadManager that can be used to
-        # download and extract URLs
-        data_path = dl_manager.download(_URL)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": data_path,
-                },
-            ),
-        ]
-
-    def _generate_examples(self, filepath):
-        """Yields examples."""
-        # TODO(coarse_discourse): Yields (key, example) tuples from the dataset
-        with open(filepath, encoding="utf-8") as f:
-            for id_, row in enumerate(f):
-                data = json.loads(row)
-                url = data.get("url", "")
-                is_self_post = data.get("is_self_post", "")
-                subreddit = data.get("subreddit", "")
-                title = data.get("title", "")
-                posts = data.get("posts", "")
-                for id1, post in enumerate(posts):
-                    maj_link = post.get("majority_link", "")
-                    maj_type = post.get("majority_type", "")
-                    id_post = post.get("id", "")
-                    is_first_post = post.get("is_firs_post", "")
-                    post_depth = post.get("post_depth", -1)
-                    in_reply_to = post.get("in_reply_to", "")
-                    annotations = post["annotations"]
-                    annotators = [annotation.get("annotator", "") for annotation in annotations]
-                    main_types = [annotation.get("main_type", "") for annotation in annotations]
-                    link_posts = [annotation.get("linkk_to_post", "") for annotation in annotations]
-
-                    yield str(id_) + "_" + str(id1), {
-                        "title": title,
-                        "is_self_post": is_self_post,
-                        "subreddit": subreddit,
-                        "url": url,
-                        "majority_link": maj_link,
-                        "is_first_post": is_first_post,
-                        "majority_type": maj_type,
-                        "id_post": id_post,
-                        "post_depth": post_depth,
-                        "in_reply_to": in_reply_to,
-                        "annotations": {"annotator": annotators, "link_to_post": link_posts, "main_type": main_types},
-                    }

data/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:03b0e10b437d8578601a698afccbbf1554a856082300385a8a0f3b59132faf5b
+size 4256575