Update files from the datasets library (from 1.17.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.17.0

dataset_infos.json

@@ -1 +1 @@
-{"plain_text": {"description": "Composed by 30 students from one of the author's undergraduate classes. These\nsentence pairs cover topics ranging from real events (e.g., Iran's plan to\nattack the Saudi ambassador to the U.S.) to events/characters in movies (e.g.,\nBatman) and purely imaginary situations, largely reflecting the pop culture as\nperceived by the American kids born in the early 90s. Each annotated example\nspans four lines: the first line contains the sentence, the second line contains\nthe target pronoun, the third line contains the two candidate antecedents, and\nthe fourth line contains the correct antecedent. If the target pronoun appears\nmore than once in the sentence, its first occurrence is the one to be resolved.\n", "citation": "@inproceedings{rahman2012resolving,\n  title={Resolving complex cases of definite pronouns: the winograd schema challenge},\n  author={Rahman, Altaf and Ng, Vincent},\n  booktitle={Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning},\n  pages={777--789},\n  year={2012},\n  organization={Association for Computational Linguistics}\n}", "homepage": "http://www.hlt.utdallas.edu/~vince/data/emnlp12/", "license": "", "features": {"sentence": {"dtype": "string", "id": null, "_type": "Value"}, "pronoun": {"dtype": "string", "id": null, "_type": "Value"}, "candidates": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": 2, "id": null, "_type": "Sequence"}, "label": {"num_classes": 2, "names": ["0", "1"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "supervised_keys": {"input": "sentence", "output": "label"}, "builder_name": "definite_pronoun_resolution", "config_name": "plain_text", "version": {"version_str": "1.0.0", "description": "", "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 72187, "num_examples": 564, "dataset_name": "definite_pronoun_resolution"}, "train": {"name": "train", "num_bytes": 172672, "num_examples": 1322, "dataset_name": "definite_pronoun_resolution"}}, "download_checksums": {"http://www.hlt.utdallas.edu/~vince/data/emnlp12/train.c.txt": {"num_bytes": 160409, "checksum": "bc0a54b3ca1009d8d5b2ca5a221086aee2b0fc5cd03b22b9dfa9cdf44c629cec"}, "http://www.hlt.utdallas.edu/~vince/data/emnlp12/test.c.txt": {"num_bytes": 67044, "checksum": "cf1cf025e1d59a5b363e6dcfbd5a13aae8a9830831ac16fd7f865aca7a1559d8"}}, "download_size": 227453, "dataset_size": 244859, "size_in_bytes": 472312}}
+{"plain_text": {"description": "Composed by 30 students from one of the author's undergraduate classes. These\nsentence pairs cover topics ranging from real events (e.g., Iran's plan to\nattack the Saudi ambassador to the U.S.) to events/characters in movies (e.g.,\nBatman) and purely imaginary situations, largely reflecting the pop culture as\nperceived by the American kids born in the early 90s. Each annotated example\nspans four lines: the first line contains the sentence, the second line contains\nthe target pronoun, the third line contains the two candidate antecedents, and\nthe fourth line contains the correct antecedent. If the target pronoun appears\nmore than once in the sentence, its first occurrence is the one to be resolved.\n", "citation": "@inproceedings{rahman2012resolving,\n  title={Resolving complex cases of definite pronouns: the winograd schema challenge},\n  author={Rahman, Altaf and Ng, Vincent},\n  booktitle={Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning},\n  pages={777--789},\n  year={2012},\n  organization={Association for Computational Linguistics}\n}", "homepage": "http://www.hlt.utdallas.edu/~vince/data/emnlp12/", "license": "", "features": {"sentence": {"dtype": "string", "id": null, "_type": "Value"}, "pronoun": {"dtype": "string", "id": null, "_type": "Value"}, "candidates": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": 2, "id": null, "_type": "Sequence"}, "label": {"num_classes": 2, "names": ["0", "1"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": {"input": "sentence", "output": "label"}, "task_templates": null, "builder_name": "definite_pronoun_resolution", "config_name": "plain_text", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 71691, "num_examples": 564, "dataset_name": "definite_pronoun_resolution"}, "train": {"name": "train", "num_bytes": 171511, "num_examples": 1322, "dataset_name": "definite_pronoun_resolution"}}, "download_checksums": {"https://s3.amazonaws.com/datasets.huggingface.co/definite_pronoun_resolution/train.c.txt": {"num_bytes": 160408, "checksum": "c310158d0cbac1a556e3284e6c167f4478271d8d50b0b9d15dfe428c905a0867"}, "https://s3.amazonaws.com/datasets.huggingface.co/definite_pronoun_resolution/test.c.txt": {"num_bytes": 67044, "checksum": "cf1cf025e1d59a5b363e6dcfbd5a13aae8a9830831ac16fd7f865aca7a1559d8"}}, "download_size": 227452, "post_processing_size": null, "dataset_size": 243202, "size_in_bytes": 470654}}

definite_pronoun_resolution.py

@@ -42,7 +42,8 @@ the fourth line contains the correct antecedent. If the target pronoun appears
 more than once in the sentence, its first occurrence is the one to be resolved.
 """
 
-_DATA_URL_PATTERN = "http://www.hlt.utdallas.edu/~vince/data/emnlp12/{}.c.txt"
+
+_DATA_URL_PATTERN = "https://s3.amazonaws.com/datasets.huggingface.co/definite_pronoun_resolution/{}.c.txt"
 
 
 class DefinitePronounResolution(datasets.GeneratorBasedBuilder):