Update files from the datasets library (from 1.17.0)

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

README.md

@@ -86,18 +86,17 @@ The data in all of the configurations looks a little different.
 A `manual` config instance consists of a sentence from the Simple English Wikipedia article, one from the linked English Wikipedia article, IDs for each of them, and a label indicating whether they are  aligned. Sentences on either side can be repeated so that the aligned sentences are in the same instances. For example:
 ```
 {'alignment_label': 1,
- 'normal_sentence': 'The Local Government Act 1985 is an Act of Parliament in the United Kingdom.',
  'normal_sentence_id': '0_66252-1-0-0',
- 'simple_sentence': 'The Local Government Act 1985 was an Act of Parliament in the United Kingdom.',
- 'simple_sentence_id': '0_66252-0-0-0'}
+ 'simple_sentence_id': '0_66252-0-0-0',
+ 'normal_sentence': 'The Local Government Act 1985 is an Act of Parliament in the United Kingdom.', 'simple_sentence': 'The Local Government Act 1985 was an Act of Parliament in the United Kingdom', 'gleu_score': 0.800000011920929}
 ```
 Is followed by
 ```
 {'alignment_label': 0,
- 'normal_sentence': 'Its main effect was to abolish the six county councils of the metropolitan counties that had been set up in 1974, 11 years earlier, by the Local Government Act 1972, along with the Greater London Council that had been established in 1965.',
  'normal_sentence_id': '0_66252-1-0-1',
- 'simple_sentence': 'The Local Government Act 1985 was an Act of Parliament in the United Kingdom.',
- 'simple_sentence_id': '0_66252-0-0-0'}
+ 'simple_sentence_id': '0_66252-0-0-0',
+ 'normal_sentence': 'Its main effect was to abolish the six county councils of the metropolitan counties that had been set up in 1974, 11 years earlier, by the Local Government Act 1972, along with the Greater London Council that had been established in 1965.',
+ 'simple_sentence': 'The Local Government Act 1985 was an Act of Parliament in the United Kingdom', 'gleu_score': 0.08641975373029709}
 ```
 
 The `auto` config shows a pair of an English and corresponding Simple English Wikipedia as an instance, with an alignment at the paragraph and sentence level:
@@ -146,9 +145,10 @@ The data has the following field:
 - `normal_sentence_id`: a unique ID for each English Wikipedia sentence. The last two dash-separated numbers correspond to the paragraph number in the article and the sentence number in the paragraph.
 - `simple_sentence`: a sentence from Simple English Wikipedia.
 - `simple_sentence_id`: a unique ID for each Simple English Wikipedia sentence. The last two dash-separated numbers correspond to the paragraph number in the article and the sentence number in the paragraph.
-- `alignment_label`: signifies whether a pair of sentences is aligned: labels are `1:aligned` and `0:notAligned`
+- `alignment_label`: signifies whether a pair of sentences is aligned: labels are `2:partialAligned`, `1:aligned` and `0:notAligned`
 - `paragraph_alignment`: a first step of alignment mapping English and Simple English paragraphs from linked articles
 - `sentence_alignment`: the full alignment mapping English and Simple English sentences from linked articles
+- `gleu_score`: the sentence level GLEU (Google-BLEU) score for each pair.
 
 ### Data Splits
 

dataset_infos.json

@@ -1 +1 @@
-{"manual": {"description": "WikiAuto provides a set of aligned sentences from English Wikipedia and Simple English Wikipedia\nas a resource to train sentence simplification systems. The authors first crowd-sourced a set of manual alignments\nbetween sentences in a subset of the Simple English Wikipedia and their corresponding versions in English Wikipedia\n(this corresponds to the `manual` config), then trained a neural CRF system to predict these alignments.\nThe trained model was then applied to the other articles in Simple English Wikipedia with an English counterpart to\ncreate a larger corpus of aligned sentences (corresponding to the `auto`, `auto_acl`, `auto_full_no_split`, and `auto_full_with_split`  configs here).\n", "citation": "@inproceedings{acl/JiangMLZX20,\n  author    = {Chao Jiang and\n               Mounica Maddela and\n               Wuwei Lan and\n               Yang Zhong and\n               Wei Xu},\n  editor    = {Dan Jurafsky and\n               Joyce Chai and\n               Natalie Schluter and\n               Joel R. Tetreault},\n  title     = {Neural {CRF} Model for Sentence Alignment in Text Simplification},\n  booktitle = {Proceedings of the 58th Annual Meeting of the Association for Computational\n               Linguistics, {ACL} 2020, Online, July 5-10, 2020},\n  pages     = {7943--7960},\n  publisher = {Association for Computational Linguistics},\n  year      = {2020},\n  url       = {https://www.aclweb.org/anthology/2020.acl-main.709/}\n}\n", "homepage": "https://github.com/chaojiang06/wiki-auto", "license": "CC-BY-SA 3.0", "features": {"alignment_label": {"num_classes": 2, "names": ["notAligned", "aligned"], "names_file": null, "id": null, "_type": "ClassLabel"}, "normal_sentence_id": {"dtype": "string", "id": null, "_type": "Value"}, "simple_sentence_id": {"dtype": "string", "id": null, "_type": "Value"}, "normal_sentence": {"dtype": "string", "id": null, "_type": "Value"}, "simple_sentence": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "wiki_auto", "config_name": "manual", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 109343271, "num_examples": 373801, "dataset_name": "wiki_auto"}, "dev": {"name": "dev", "num_bytes": 20819779, "num_examples": 73249, "dataset_name": "wiki_auto"}, "test": {"name": "test", "num_bytes": 33379338, "num_examples": 118074, "dataset_name": "wiki_auto"}}, "download_checksums": {"https://github.com/chaojiang06/wiki-auto/raw/master/wiki-manual/train.tsv": {"num_bytes": 106346588, "checksum": "82fa388de3ded6d303b95fcd11ba70e0b6158d2df1cbf24913bb54503bd32e95"}, "https://github.com/chaojiang06/wiki-auto/raw/master/wiki-manual/dev.tsv": {"num_bytes": 20232621, "checksum": "c56a9d2a739f9da83f90c54e266e1d60dd036cb80c463f118cb55613232e2e41"}, "https://github.com/chaojiang06/wiki-auto/raw/master/wiki-manual/test.tsv": {"num_bytes": 32432523, "checksum": "ab8b818b0eeb7aa7712d244ee0ea16cfd915a896c40f02a34a808b597a5e68a0"}}, "download_size": 159011732, "post_processing_size": null, "dataset_size": 163542388, "size_in_bytes": 322554120}, "auto_acl": {"description": "WikiAuto provides a set of aligned sentences from English Wikipedia and Simple English Wikipedia\nas a resource to train sentence simplification systems. 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Tetreault},\n  title     = {Neural {CRF} Model for Sentence Alignment in Text Simplification},\n  booktitle = {Proceedings of the 58th Annual Meeting of the Association for Computational\n               Linguistics, {ACL} 2020, Online, July 5-10, 2020},\n  pages     = {7943--7960},\n  publisher = {Association for Computational Linguistics},\n  year      = {2020},\n  url       = {https://www.aclweb.org/anthology/2020.acl-main.709/}\n}\n", "homepage": "https://github.com/chaojiang06/wiki-auto", "license": "CC-BY-SA 3.0", "features": {"example_id": {"dtype": "string", "id": null, "_type": "Value"}, "normal": {"normal_article_id": {"dtype": "int32", "id": null, "_type": "Value"}, "normal_article_title": {"dtype": "string", "id": null, "_type": "Value"}, "normal_article_url": {"dtype": "string", "id": null, "_type": "Value"}, "normal_article_content": {"feature": {"normal_sentence_id": {"dtype": "string", "id": null, "_type": "Value"}, "normal_sentence": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "simple": {"simple_article_id": {"dtype": "int32", "id": null, "_type": "Value"}, "simple_article_title": {"dtype": "string", "id": null, "_type": "Value"}, "simple_article_url": {"dtype": "string", "id": null, "_type": "Value"}, "simple_article_content": {"feature": {"simple_sentence_id": {"dtype": "string", "id": null, "_type": "Value"}, "simple_sentence": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "paragraph_alignment": {"feature": {"normal_paragraph_id": {"dtype": "string", "id": null, "_type": "Value"}, "simple_paragraph_id": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "sentence_alignment": {"feature": {"normal_sentence_id": {"dtype": "string", "id": null, "_type": "Value"}, "simple_sentence_id": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "wiki_auto", "config_name": "auto", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"part_1": {"name": "part_1", "num_bytes": 1773240295, "num_examples": 125059, "dataset_name": "wiki_auto"}, "part_2": {"name": "part_2", "num_bytes": 80417651, "num_examples": 13036, "dataset_name": "wiki_auto"}}, "download_checksums": {"https://www.dropbox.com/sh/ohqaw41v48c7e5p/AAATBDhU1zpdcT5x5WgO8DMaa/wiki-auto-all-data/wiki-auto-part-1-data.json?dl=1": {"num_bytes": 2067424750, "checksum": "136d8e113a773d3669228a57cae733fca079954daf0b3514505410c66d1a69b6"}, "https://www.dropbox.com/sh/ohqaw41v48c7e5p/AAATgPkjo_tPt9z12vZxJ3MRa/wiki-auto-all-data/wiki-auto-part-2-data.json?dl=1": {"num_bytes": 93214171, "checksum": "94b33a11447c121a0ce7293de20fb969c36d8a62b31afc5873a4174ed17a1d4e"}}, "download_size": 2160638921, "post_processing_size": null, "dataset_size": 1853657946, "size_in_bytes": 4014296867}, "auto_full_no_split": {"description": "WikiAuto provides a set of aligned sentences from English Wikipedia and Simple English Wikipedia\nas a resource to train sentence simplification systems. The authors first crowd-sourced a set of manual alignments\nbetween sentences in a subset of the Simple English Wikipedia and their corresponding versions in English Wikipedia\n(this corresponds to the `manual` config), then trained a neural CRF system to predict these alignments.\nThe trained model was then applied to the other articles in Simple English Wikipedia with an English counterpart to\ncreate a larger corpus of aligned sentences (corresponding to the `auto`, `auto_acl`, `auto_full_no_split`, and `auto_full_with_split`  configs here).\n", "citation": "@inproceedings{acl/JiangMLZX20,\n  author    = {Chao Jiang and\n               Mounica Maddela and\n               Wuwei Lan and\n               Yang Zhong and\n               Wei Xu},\n  editor    = {Dan Jurafsky and\n               Joyce Chai and\n               Natalie Schluter and\n               Joel R. Tetreault},\n  title     = {Neural {CRF} Model for Sentence Alignment in Text Simplification},\n  booktitle = {Proceedings of the 58th Annual Meeting of the Association for Computational\n               Linguistics, {ACL} 2020, Online, July 5-10, 2020},\n  pages     = {7943--7960},\n  publisher = {Association for Computational Linguistics},\n  year      = {2020},\n  url       = {https://www.aclweb.org/anthology/2020.acl-main.709/}\n}\n", "homepage": "https://github.com/chaojiang06/wiki-auto", "license": "CC-BY-SA 3.0", "features": {"normal_sentence": {"dtype": "string", "id": null, "_type": "Value"}, "simple_sentence": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "wiki_auto", "config_name": "auto_full_no_split", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"full": {"name": "full", "num_bytes": 146310611, "num_examples": 591994, "dataset_name": "wiki_auto"}}, "download_checksums": {"https://github.com/chaojiang06/wiki-auto/raw/master/wiki-auto/GEM2021/full_no_split/train.src": {"num_bytes": 86028898, "checksum": "48d820fc1e7bd7121edde04a2aedf62bb9069b9caed01b77b7cb3852cc6b33d0"}, "https://github.com/chaojiang06/wiki-auto/raw/master/wiki-auto/GEM2021/full_no_split/train.dst": {"num_bytes": 55545281, "checksum": "37b373c5ee8c3f4b844c9896f07fb6bb55a20a3d4a8e1a6b06a651b87a653415"}}, "download_size": 141574179, "post_processing_size": null, "dataset_size": 146310611, "size_in_bytes": 287884790}, "auto_full_with_split": {"description": "WikiAuto provides a set of aligned sentences from English Wikipedia and Simple English Wikipedia\nas a resource to train sentence simplification systems. The authors first crowd-sourced a set of manual alignments\nbetween sentences in a subset of the Simple English Wikipedia and their corresponding versions in English Wikipedia\n(this corresponds to the `manual` config), then trained a neural CRF system to predict these alignments.\nThe trained model was then applied to the other articles in Simple English Wikipedia with an English counterpart to\ncreate a larger corpus of aligned sentences (corresponding to the `auto`, `auto_acl`, `auto_full_no_split`, and `auto_full_with_split`  configs here).\n", "citation": "@inproceedings{acl/JiangMLZX20,\n  author    = {Chao Jiang and\n               Mounica Maddela and\n               Wuwei Lan and\n               Yang Zhong and\n               Wei Xu},\n  editor    = {Dan Jurafsky and\n               Joyce Chai and\n               Natalie Schluter and\n               Joel R. Tetreault},\n  title     = {Neural {CRF} Model for Sentence Alignment in Text Simplification},\n  booktitle = {Proceedings of the 58th Annual Meeting of the Association for Computational\n               Linguistics, {ACL} 2020, Online, July 5-10, 2020},\n  pages     = {7943--7960},\n  publisher = {Association for Computational Linguistics},\n  year      = {2020},\n  url       = {https://www.aclweb.org/anthology/2020.acl-main.709/}\n}\n", "homepage": "https://github.com/chaojiang06/wiki-auto", "license": "CC-BY-SA 3.0", "features": {"normal_sentence": {"dtype": "string", "id": null, "_type": "Value"}, "simple_sentence": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "wiki_auto", "config_name": "auto_full_with_split", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"full": {"name": "full", "num_bytes": 124549115, "num_examples": 483801, "dataset_name": "wiki_auto"}}, "download_checksums": {"https://github.com/chaojiang06/wiki-auto/raw/master/wiki-auto/GEM2021/full_with_split/train.src": {"num_bytes": 67389841, "checksum": "f70dd6083bf679254dfd6c1e14960ad2b526bc35596d9c87b0c636c0285ce8ac"}, "https://github.com/chaojiang06/wiki-auto/raw/master/wiki-auto/GEM2021/full_with_split/train.dst": {"num_bytes": 53288474, "checksum": "74529cfc316c8a3ed7720f87e25d0758620e0e838a5747ec4a1bbdccef018f75"}}, "download_size": 120678315, "post_processing_size": null, "dataset_size": 124549115, "size_in_bytes": 245227430}}

dummy/manual/1.0.0/dummy_data.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:15067eb8b69bc1ef83aea73549346e45d92f56d41b77b08c06f8b404f0f2de14
-size 1801
+oid sha256:a7f9712718145ba7197e38d9cf31a73db59a2d92d31bd8b6dca684643cc405f4
+size 2043

wiki_auto.py

@@ -60,7 +60,7 @@ _LICENSE = "CC-BY-SA 3.0"
 # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
 _URLs = {
     "manual": {
-        "train": "https://github.com/chaojiang06/wiki-auto/raw/master/wiki-manual/train.tsv",
+        "train": "https://www.dropbox.com/sh/ohqaw41v48c7e5p/AACdl4UPKtu7CMMa-CJhz4G7a/wiki-manual/train.tsv?dl=1",
         "dev": "https://github.com/chaojiang06/wiki-auto/raw/master/wiki-manual/dev.tsv",
         "test": "https://github.com/chaojiang06/wiki-auto/raw/master/wiki-manual/test.tsv",
     },
@@ -77,8 +77,8 @@ _URLs = {
         "simple": "https://github.com/chaojiang06/wiki-auto/raw/master/wiki-auto/GEM2021/full_with_split/train.dst",
     },
     "auto": {
-        "part_1": "https://github.com/chaojiang06/wiki-auto/raw/master/wiki-auto/all_data/wiki-auto-part-1-data.json",
-        "part_2": "https://github.com/chaojiang06/wiki-auto/raw/master/wiki-auto/all_data/wiki-auto-part-2-data.json",
+        "part_1": "https://www.dropbox.com/sh/ohqaw41v48c7e5p/AAATBDhU1zpdcT5x5WgO8DMaa/wiki-auto-all-data/wiki-auto-part-1-data.json?dl=1",
+        "part_2": "https://www.dropbox.com/sh/ohqaw41v48c7e5p/AAATgPkjo_tPt9z12vZxJ3MRa/wiki-auto-all-data/wiki-auto-part-2-data.json?dl=1",
     },
 }
 
@@ -121,11 +121,12 @@ class WikiAuto(datasets.GeneratorBasedBuilder):
         if self.config.name == "manual":  # This is the name of the configuration selected in BUILDER_CONFIGS above
             features = datasets.Features(
                 {
-                    "alignment_label": datasets.ClassLabel(names=["notAligned", "aligned"]),
+                    "alignment_label": datasets.ClassLabel(names=["notAligned", "aligned", "partialAligned"]),
                     "normal_sentence_id": datasets.Value("string"),
                     "simple_sentence_id": datasets.Value("string"),
                     "normal_sentence": datasets.Value("string"),
                     "simple_sentence": datasets.Value("string"),
+                    "gleu_score": datasets.Value("float32"),
                 }
             )
         elif (
@@ -218,12 +219,15 @@ class WikiAuto(datasets.GeneratorBasedBuilder):
                 "normal_sentence_id",
                 "simple_sentence",
                 "normal_sentence",
+                "gleu_score",
             ]
             with open(filepaths[split], encoding="utf-8") as f:
                 for id_, line in enumerate(f):
                     values = line.strip().split("\t")
-                    assert len(values) == 5, f"Not enough fields in ---- {line} --- {values}"
-                    yield id_, dict([(k, val) for k, val in zip(keys, values)])
+                    assert len(values) == 6, f"Not enough fields in ---- {line} --- {values}"
+                    yield id_, dict(
+                        [(k, val) if k != "gleu_score" else (k, float(val)) for k, val in zip(keys, values)]
+                    )
         elif (
             self.config.name == "auto_acl"
             or self.config.name == "auto_full_no_split"