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Update files from the datasets library (from 1.8.0)

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Release notes: https://github.com/huggingface/datasets/releases/tag/1.8.0

Files changed (3) hide show
  1. README.md +22 -3
  2. dataset_infos.json +1 -1
  3. squad_it.py +6 -0
README.md CHANGED
@@ -1,4 +1,23 @@
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  paperswithcode_id: squad-it
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  ---
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@@ -91,9 +110,9 @@ The data fields are the same among all splits.
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  ### Data Splits
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- | name |train|test|
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- |-------|----:|---:|
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- |default|54159|7609|
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  ## Dataset Creation
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  ---
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+ annotations_creators:
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+ - machine-generated
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+ language_creators:
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+ - machine-generated
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+ languages:
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+ - it-IT
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+ licenses:
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+ - unknown
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+ multilinguality:
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+ - monolingual
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+ size_categories:
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+ - unknown
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+ source_datasets:
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+ - extended|squad
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+ task_categories:
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+ - question-answering
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+ task_ids:
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+ - open-domain-qa
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+ - extractive-qa
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  paperswithcode_id: squad-it
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  ---
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  ### Data Splits
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+ | name | train | test |
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+ | ------- | ----: | ---: |
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+ | default | 54159 | 7609 |
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  ## Dataset Creation
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dataset_infos.json CHANGED
@@ -1 +1 @@
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- {"default": {"description": "SQuAD-it is derived from the SQuAD dataset and it is obtained through semi-automatic translation of the SQuAD dataset \ninto Italian. It represents a large-scale dataset for open question answering processes on factoid questions in Italian.\n The dataset contains more than 60,000 question/answer pairs derived from the original English dataset. The dataset is \n split into training and test sets to support the replicability of the benchmarking of QA systems:\n", "citation": "@InProceedings{10.1007/978-3-030-03840-3_29,\n\tauthor=\"Croce, Danilo and Zelenanska, Alexandra and Basili, Roberto\",\n\teditor=\"Ghidini, Chiara and Magnini, Bernardo and Passerini, Andrea and Traverso, Paolo\",\n\ttitle=\"Neural Learning for Question Answering in Italian\",\n\tbooktitle=\"AI*IA 2018 -- Advances in Artificial Intelligence\",\n\tyear=\"2018\",\n\tpublisher=\"Springer International Publishing\",\n\taddress=\"Cham\",\n\tpages=\"389--402\",\n\tisbn=\"978-3-030-03840-3\"\n}\n", "homepage": "https://github.com/crux82/squad-it", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "context": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "answers": {"feature": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "answer_start": {"dtype": "int32", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "supervised_keys": null, "builder_name": "squad_it", "config_name": "default", "version": {"version_str": "0.1.0", "description": null, "datasets_version_to_prepare": null, "major": 0, "minor": 1, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 7870374, "num_examples": 7609, "dataset_name": "squad_it"}, "train": {"name": "train", "num_bytes": 50925634, "num_examples": 54159, "dataset_name": "squad_it"}}, "download_checksums": {"https://github.com/crux82/squad-it/raw/master/SQuAD_it-train.json.gz": {"num_bytes": 7725286, "checksum": "75d4d2832961f7a0f76a43d7e919e56a880ccc55de434ec90ae82cd67bec5d25"}, "https://github.com/crux82/squad-it/raw/master/SQuAD_it-test.json.gz": {"num_bytes": 1051245, "checksum": "25986c617cc7d58e82e916755b8a5684e5efae69835332858a6534a304cd293c"}}, "download_size": 8776531, "dataset_size": 58796008, "size_in_bytes": 67572539}}
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+ {"default": {"description": "SQuAD-it is derived from the SQuAD dataset and it is obtained through semi-automatic translation of the SQuAD dataset\ninto Italian. It represents a large-scale dataset for open question answering processes on factoid questions in Italian.\n The dataset contains more than 60,000 question/answer pairs derived from the original English dataset. The dataset is\n split into training and test sets to support the replicability of the benchmarking of QA systems:\n", "citation": "@InProceedings{10.1007/978-3-030-03840-3_29,\n author={Croce, Danilo and Zelenanska, Alexandra and Basili, Roberto},\n editor={Ghidini, Chiara and Magnini, Bernardo and Passerini, Andrea and Traverso, Paolo\",\n title={Neural Learning for Question Answering in Italian},\n booktitle={AI*IA 2018 -- Advances in Artificial Intelligence},\n year={2018},\n publisher={Springer International Publishing},\n address={Cham},\n pages={389--402},\n isbn={978-3-030-03840-3}\n}\n", "homepage": "https://github.com/crux82/squad-it", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "context": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "answers": {"feature": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "answer_start": {"dtype": "int32", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": [{"task": "question-answering-extractive", "question_column": "question", "context_column": "context", "answers_column": "answers"}], "builder_name": "squad_it", "config_name": "default", "version": {"version_str": "0.1.0", "description": null, "major": 0, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 50864824, "num_examples": 54159, "dataset_name": "squad_it"}, "test": {"name": "test", "num_bytes": 7858336, "num_examples": 7609, "dataset_name": "squad_it"}}, "download_checksums": {"https://github.com/crux82/squad-it/raw/master/SQuAD_it-train.json.gz": {"num_bytes": 7725286, "checksum": "75d4d2832961f7a0f76a43d7e919e56a880ccc55de434ec90ae82cd67bec5d25"}, "https://github.com/crux82/squad-it/raw/master/SQuAD_it-test.json.gz": {"num_bytes": 1051245, "checksum": "25986c617cc7d58e82e916755b8a5684e5efae69835332858a6534a304cd293c"}}, "download_size": 8776531, "post_processing_size": null, "dataset_size": 58723160, "size_in_bytes": 67499691}}
squad_it.py CHANGED
@@ -4,6 +4,7 @@
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  import json
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  import datasets
 
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  # TODO(squad_it): BibTeX citation
@@ -69,6 +70,11 @@ class SquadIt(datasets.GeneratorBasedBuilder):
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  # Homepage of the dataset for documentation
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  homepage="https://github.com/crux82/squad-it",
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  citation=_CITATION,
 
 
 
 
 
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  )
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  def _split_generators(self, dl_manager):
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  import json
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  import datasets
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+ from datasets.tasks import QuestionAnsweringExtractive
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  # TODO(squad_it): BibTeX citation
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  # Homepage of the dataset for documentation
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  homepage="https://github.com/crux82/squad-it",
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  citation=_CITATION,
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+ task_templates=[
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+ QuestionAnsweringExtractive(
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+ question_column="question", context_column="context", answers_column="answers"
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+ )
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+ ],
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  )
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  def _split_generators(self, dl_manager):