albertvillanova HF staff orsharir commited on
Commit
921e4b3
1 Parent(s): e990675

Fix URL for the validation split (#4)

Browse files

- The URL for the validation set was previously pointed toward to the training set. Fixed to correct URL. (563edc818b5f855ea451913ac4a2b92cc0162bb4)
- Update checksums and sizes for the new files (d22e4f7c16dad1ab83621aab87ffe7f81e5c2023)
- Bump versions (85f680a6c074232322808a2b71ddca61fd98bf34)
- Update README.md according to validation split (706b69e1efe01f8bf55feb8e2b6bf531f7ed99ae)


Co-authored-by: Or Sharir <[email protected]>

README.md CHANGED
@@ -65,8 +65,8 @@ dataset_info:
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  num_bytes: 2805711609
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  num_examples: 600000
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  - name: validation
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- num_bytes: 2805711609
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- num_examples: 600000
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  download_size: 1003195420
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  dataset_size: 5611423218
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  ---
@@ -198,7 +198,7 @@ The data fields are the same among all splits.
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  | |train |validation|
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  |-----------|-----:|---------:|
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- |bypublisher|600000| 600000|
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  ## Dataset Creation
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  num_bytes: 2805711609
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  num_examples: 600000
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  - name: validation
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+ num_bytes: 960356598
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+ num_examples: 150000
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  download_size: 1003195420
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  dataset_size: 5611423218
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  ---
 
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  | |train |validation|
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  |-----------|-----:|---------:|
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+ |bypublisher|600000| 150000|
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  ## Dataset Creation
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dataset_infos.json CHANGED
@@ -1 +1 @@
1
- {"byarticle": {"description": "Hyperpartisan News Detection was a dataset created for PAN @ SemEval 2019 Task 4.\nGiven a news article text, decide whether it follows a hyperpartisan argumentation, i.e., whether it exhibits blind, prejudiced, or unreasoning allegiance to one party, faction, cause, or person.\n\nThere are 2 parts:\n- byarticle: Labeled through crowdsourcing on an article basis. The data contains only articles for which a consensus among the crowdsourcing workers existed.\n- bypublisher: Labeled by the overall bias of the publisher as provided by BuzzFeed journalists or MediaBiasFactCheck.com.\n", "citation": "@article{kiesel2019data,\n title={Data for pan at semeval 2019 task 4: Hyperpartisan news detection},\n author={Kiesel, Johannes and Mestre, Maria and Shukla, Rishabh and Vincent, Emmanuel and Corney, David and Adineh, Payam and Stein, Benno and Potthast, Martin},\n year={2019}\n}\n", "homepage": "https://pan.webis.de/semeval19/semeval19-web/", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "hyperpartisan": {"dtype": "bool", "id": null, "_type": "Value"}, "url": {"dtype": "string", "id": null, "_type": "Value"}, "published_at": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": {"features": null, "resources_checksums": {"train": {}}}, "supervised_keys": {"input": "text", "output": "label"}, "builder_name": "hyperpartisan_news_detection", "config_name": "byarticle", "version": {"version_str": "1.0.0", "description": "Version Training and validation v1", "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2803943, "num_examples": 645, "dataset_name": "hyperpartisan_news_detection"}}, "download_checksums": {"https://zenodo.org/record/1489920/files/articles-training-byarticle-20181122.zip?download=1": {"num_bytes": 971841, "checksum": "62b4a71275ef2724faddc74d6ff3d782ee9898c732cd66119c7976f6f5168990"}, "https://zenodo.org/record/1489920/files/ground-truth-training-byarticle-20181122.zip?download=1": {"num_bytes": 28511, "checksum": "0c02f4c33317287758e6fbbc976cbfd7a0978923899ddf30cb9dd2cd740af43c"}}, "download_size": 1000352, "post_processing_size": 0, "dataset_size": 2803943, "size_in_bytes": 3804295}, "bypublisher": {"description": "Hyperpartisan News Detection was a dataset created for PAN @ SemEval 2019 Task 4.\nGiven a news article text, decide whether it follows a hyperpartisan argumentation, i.e., whether it exhibits blind, prejudiced, or unreasoning allegiance to one party, faction, cause, or person.\n\nThere are 2 parts:\n- byarticle: Labeled through crowdsourcing on an article basis. The data contains only articles for which a consensus among the crowdsourcing workers existed.\n- bypublisher: Labeled by the overall bias of the publisher as provided by BuzzFeed journalists or MediaBiasFactCheck.com.\n", "citation": "@article{kiesel2019data,\n title={Data for pan at semeval 2019 task 4: Hyperpartisan news detection},\n author={Kiesel, Johannes and Mestre, Maria and Shukla, Rishabh and Vincent, Emmanuel and Corney, David and Adineh, Payam and Stein, Benno and Potthast, Martin},\n year={2019}\n}\n", "homepage": "https://pan.webis.de/semeval19/semeval19-web/", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "hyperpartisan": {"dtype": "bool", "id": null, "_type": "Value"}, "url": {"dtype": "string", "id": null, "_type": "Value"}, "published_at": {"dtype": "string", "id": null, "_type": "Value"}, "bias": {"num_classes": 5, "names": ["right", "right-center", "least", "left-center", "left"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": {"features": null, "resources_checksums": {"train": {}, "validation": {}}}, "supervised_keys": {"input": "text", "output": "label"}, "builder_name": "hyperpartisan_news_detection", "config_name": "bypublisher", "version": {"version_str": "1.0.0", "description": "Version Training and validation v1", "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2805711609, "num_examples": 600000, "dataset_name": "hyperpartisan_news_detection"}, "validation": {"name": "validation", "num_bytes": 2805711609, "num_examples": 600000, "dataset_name": "hyperpartisan_news_detection"}}, "download_checksums": {"https://zenodo.org/record/1489920/files/articles-training-bypublisher-20181122.zip?download=1": {"num_bytes": 980769009, "checksum": "e5816b0c9fecd1a38f6cba8eb4f6f77d04637b5c6209e714b7ab32dc3bc24e28"}, "https://zenodo.org/record/1489920/files/ground-truth-training-bypublisher-20181122.zip?download=1": {"num_bytes": 22426411, "checksum": "f1c0494af86ff1e961479a63d432d649ccda875d302888f4d080dbec0382b1ef"}}, "download_size": 1003195420, "post_processing_size": 0, "dataset_size": 5611423218, "size_in_bytes": 6614618638}}
 
1
+ {"byarticle": {"description": "Hyperpartisan News Detection was a dataset created for PAN @ SemEval 2019 Task 4.\nGiven a news article text, decide whether it follows a hyperpartisan argumentation, i.e., whether it exhibits blind, prejudiced, or unreasoning allegiance to one party, faction, cause, or person.\n\nThere are 2 parts:\n- byarticle: Labeled through crowdsourcing on an article basis. The data contains only articles for which a consensus among the crowdsourcing workers existed.\n- bypublisher: Labeled by the overall bias of the publisher as provided by BuzzFeed journalists or MediaBiasFactCheck.com.\n", "citation": "@article{kiesel2019data,\n title={Data for pan at semeval 2019 task 4: Hyperpartisan news detection},\n author={Kiesel, Johannes and Mestre, Maria and Shukla, Rishabh and Vincent, Emmanuel and Corney, David and Adineh, Payam and Stein, Benno and Potthast, Martin},\n year={2019}\n}\n", "homepage": "https://pan.webis.de/semeval19/semeval19-web/", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "hyperpartisan": {"dtype": "bool", "id": null, "_type": "Value"}, "url": {"dtype": "string", "id": null, "_type": "Value"}, "published_at": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": {"features": null, "resources_checksums": {"train": {}}}, "supervised_keys": {"input": "text", "output": "label"}, "builder_name": "hyperpartisan_news_detection", "config_name": "byarticle", "version": {"version_str": "1.0.0", "description": "Version Training and validation v1", "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2803943, "num_examples": 645, "dataset_name": "hyperpartisan_news_detection"}}, "download_checksums": {"https://zenodo.org/record/1489920/files/articles-training-byarticle-20181122.zip?download=1": {"num_bytes": 971841, "checksum": "62b4a71275ef2724faddc74d6ff3d782ee9898c732cd66119c7976f6f5168990"}, "https://zenodo.org/record/1489920/files/ground-truth-training-byarticle-20181122.zip?download=1": {"num_bytes": 28511, "checksum": "0c02f4c33317287758e6fbbc976cbfd7a0978923899ddf30cb9dd2cd740af43c"}}, "download_size": 1000352, "post_processing_size": 0, "dataset_size": 2803943, "size_in_bytes": 3804295}, "bypublisher": {"description": "Hyperpartisan News Detection was a dataset created for PAN @ SemEval 2019 Task 4.\nGiven a news article text, decide whether it follows a hyperpartisan argumentation, i.e., whether it exhibits blind, prejudiced, or unreasoning allegiance to one party, faction, cause, or person.\n\nThere are 2 parts:\n- byarticle: Labeled through crowdsourcing on an article basis. The data contains only articles for which a consensus among the crowdsourcing workers existed.\n- bypublisher: Labeled by the overall bias of the publisher as provided by BuzzFeed journalists or MediaBiasFactCheck.com.\n", "citation": "@article{kiesel2019data,\n title={Data for pan at semeval 2019 task 4: Hyperpartisan news detection},\n author={Kiesel, Johannes and Mestre, Maria and Shukla, Rishabh and Vincent, Emmanuel and Corney, David and Adineh, Payam and Stein, Benno and Potthast, Martin},\n year={2019}\n}\n", "homepage": "https://pan.webis.de/semeval19/semeval19-web/", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "hyperpartisan": {"dtype": "bool", "id": null, "_type": "Value"}, "url": {"dtype": "string", "id": null, "_type": "Value"}, "published_at": {"dtype": "string", "id": null, "_type": "Value"}, "bias": {"num_classes": 5, "names": ["right", "right-center", "least", "left-center", "left"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": {"features": null, "resources_checksums": {"train": {}, "validation": {}}}, "supervised_keys": {"input": "text", "output": "label"}, "builder_name": "hyperpartisan_news_detection", "config_name": "bypublisher", "version": {"version_str": "1.0.1", "description": "Version Training and validation v1", "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 1}, "splits": {"train": {"name": "train", "num_bytes": 2805711609, "num_examples": 600000, "dataset_name": "hyperpartisan_news_detection"}, "validation": {"name": "validation", "num_bytes": 960356598, "num_examples": 150000, "dataset_name": "hyperpartisan_news_detection"}}, "download_checksums": {"https://zenodo.org/record/1489920/files/articles-training-bypublisher-20181122.zip?download=1": {"num_bytes": 980769009, "checksum": "e5816b0c9fecd1a38f6cba8eb4f6f77d04637b5c6209e714b7ab32dc3bc24e28"}, "https://zenodo.org/record/1489920/files/ground-truth-training-bypublisher-20181122.zip?download=1": {"num_bytes": 22426411, "checksum": "f1c0494af86ff1e961479a63d432d649ccda875d302888f4d080dbec0382b1ef"}, "https://zenodo.org/record/1489920/files/articles-validation-bypublisher-20181122.zip?download=1": {"num_bytes": 337386275, "checksum": "dd1cd3d7f34d7f35564ba2b7002cad796877507bec503cc1dd02076dc289ae34"}, "https://zenodo.org/record/1489920/files/ground-truth-validation-bypublisher-20181122.zip?download=1": {"num_bytes": 5239324, "checksum": "23f7cd8b410a91193e2b6548ba274d7da1061ea7c86083e9b5ced4cac9bb34e7"}}, "download_size": 1345821019, "post_processing_size": 0, "dataset_size": 3766068207, "size_in_bytes": 6614618638}}
hyperpartisan_news_detection.py CHANGED
@@ -46,7 +46,7 @@ _URL_BASE = "https://zenodo.org/record/1489920/files/"
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  class HyperpartisanNewsDetection(datasets.GeneratorBasedBuilder):
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  """Hyperpartisan News Detection Dataset."""
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- VERSION = datasets.Version("1.0.0")
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  BUILDER_CONFIGS = [
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  datasets.BuilderConfig(
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  name="byarticle",
@@ -62,7 +62,7 @@ class HyperpartisanNewsDetection(datasets.GeneratorBasedBuilder):
62
  ),
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  datasets.BuilderConfig(
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  name="bypublisher",
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- version=datasets.Version("1.0.0", "Version Training and validation v1"),
66
  description=textwrap.dedent(
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  """
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  This part of the data (filename contains "bypublisher") is labeled by the overall bias of the publisher as provided
@@ -107,8 +107,8 @@ class HyperpartisanNewsDetection(datasets.GeneratorBasedBuilder):
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  }
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  if self.config.name == "bypublisher":
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  urls[datasets.Split.VALIDATION] = {
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- "articles_file": _URL_BASE + "articles-training-" + self.config.name + "-20181122.zip?download=1",
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- "labels_file": _URL_BASE + "ground-truth-training-" + self.config.name + "-20181122.zip?download=1",
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  }
113
 
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  data_dir = {}
 
46
  class HyperpartisanNewsDetection(datasets.GeneratorBasedBuilder):
47
  """Hyperpartisan News Detection Dataset."""
48
 
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+ VERSION = datasets.Version("1.0.1")
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  BUILDER_CONFIGS = [
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  datasets.BuilderConfig(
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  name="byarticle",
 
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  ),
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  datasets.BuilderConfig(
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  name="bypublisher",
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+ version=datasets.Version("1.0.1", "Version Training and validation v1"),
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  description=textwrap.dedent(
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  """
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  This part of the data (filename contains "bypublisher") is labeled by the overall bias of the publisher as provided
 
107
  }
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  if self.config.name == "bypublisher":
109
  urls[datasets.Split.VALIDATION] = {
110
+ "articles_file": _URL_BASE + "articles-validation-" + self.config.name + "-20181122.zip?download=1",
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+ "labels_file": _URL_BASE + "ground-truth-validation-" + self.config.name + "-20181122.zip?download=1",
112
  }
113
 
114
  data_dir = {}