Update files from the datasets library (from 1.18.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.18.0

README.md

@@ -6,7 +6,7 @@ language_creators:
 languages:
 - en
 licenses:
-- unknown
+- other
 multilinguality:
 - monolingual
 size_categories:
@@ -196,7 +196,21 @@ The data fields are the same among all splits.
 
 ### Licensing Information
 
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+From the [CoNLL2003 shared task](https://www.clips.uantwerpen.be/conll2003/ner/) page:
+
+> The English data is a collection of news wire articles from the Reuters Corpus. The annotation has been done by people of the University of Antwerp. Because of copyright reasons we only make available the annotations. In order to build the complete data sets you will need access to the Reuters Corpus. It can be obtained for research purposes without any charge from NIST.
+
+The copyrights are defined below, from the [Reuters Corpus page](https://trec.nist.gov/data/reuters/reuters.html):
+
+> The stories in the Reuters Corpus are under the copyright of Reuters Ltd and/or Thomson Reuters, and their use is governed by the following agreements:
+>
+> [Organizational agreement](https://trec.nist.gov/data/reuters/org_appl_reuters_v4.html)
+>
+> This agreement must be signed by the person responsible for the data at your organization, and sent to NIST.
+>
+> [Individual agreement](https://trec.nist.gov/data/reuters/ind_appl_reuters_v4.html)
+>
+> This agreement must be signed by all researchers using the Reuters Corpus at your organization, and kept on file at your organization.
 
 ### Citation Information
 

conll2003.py

@@ -16,6 +16,8 @@
 # Lint as: python3
 """Introduction to the CoNLL-2003 Shared Task: Language-Independent Named Entity Recognition"""
 
+import os
+
 import datasets
 
 
@@ -50,7 +52,7 @@ tagging scheme, whereas the original dataset uses IOB1.
 For more details see https://www.clips.uantwerpen.be/conll2003/ner/ and https://www.aclweb.org/anthology/W03-0419
 """
 
-_URL = "https://github.com/davidsbatista/NER-datasets/raw/master/CONLL2003/"
+_URL = "https://data.deepai.org/conll2003.zip"
 _TRAINING_FILE = "train.txt"
 _DEV_FILE = "valid.txt"
 _TEST_FILE = "test.txt"
@@ -188,17 +190,17 @@ class Conll2003(datasets.GeneratorBasedBuilder):
 
     def _split_generators(self, dl_manager):
         """Returns SplitGenerators."""
-        urls_to_download = {
-            "train": f"{_URL}{_TRAINING_FILE}",
-            "dev": f"{_URL}{_DEV_FILE}",
-            "test": f"{_URL}{_TEST_FILE}",
+        downloaded_file = dl_manager.download_and_extract(_URL)
+        data_files = {
+            "train": os.path.join(downloaded_file, _TRAINING_FILE),
+            "dev": os.path.join(downloaded_file, _DEV_FILE),
+            "test": os.path.join(downloaded_file, _TEST_FILE),
         }
-        downloaded_files = dl_manager.download_and_extract(urls_to_download)
 
         return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_files["train"]}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": data_files["dev"]}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": data_files["test"]}),
         ]
 
     def _generate_examples(self, filepath):

dataset_infos.json

@@ -1 +1 @@
-{"conll2003": {"description": "The shared task of CoNLL-2003 concerns language-independent named entity recognition. We will concentrate on\nfour types of named entities: persons, locations, organizations and names of miscellaneous entities that do\nnot belong to the previous three groups.\n\nThe CoNLL-2003 shared task data files contain four columns separated by a single space. Each word has been put on\na separate line and there is an empty line after each sentence. The first item on each line is a word, the second\na part-of-speech (POS) tag, the third a syntactic chunk tag and the fourth the named entity tag. The chunk tags\nand the named entity tags have the format I-TYPE which means that the word is inside a phrase of type TYPE. Only\nif two phrases of the same type immediately follow each other, the first word of the second phrase will have tag\nB-TYPE to show that it starts a new phrase. A word with tag O is not part of a phrase. Note the dataset uses IOB2\ntagging scheme, whereas the original dataset uses IOB1.\n\nFor more details see https://www.clips.uantwerpen.be/conll2003/ner/ and https://www.aclweb.org/anthology/W03-0419\n", "citation": "@inproceedings{tjong-kim-sang-de-meulder-2003-introduction,\n    title = \"Introduction to the {C}o{NLL}-2003 Shared Task: Language-Independent Named Entity Recognition\",\n    author = \"Tjong Kim Sang, Erik F.  and\n      De Meulder, Fien\",\n    booktitle = \"Proceedings of the Seventh Conference on Natural Language Learning at {HLT}-{NAACL} 2003\",\n    year = \"2003\",\n    url = \"https://www.aclweb.org/anthology/W03-0419\",\n    pages = \"142--147\",\n}\n", "homepage": "https://www.aclweb.org/anthology/W03-0419/", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "tokens": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "pos_tags": {"feature": {"num_classes": 47, "names": ["\"", "''", "#", "$", "(", ")", ",", ".", ":", "``", "CC", "CD", "DT", "EX", "FW", "IN", "JJ", "JJR", "JJS", "LS", "MD", "NN", "NNP", "NNPS", "NNS", "NN|SYM", "PDT", "POS", "PRP", "PRP$", "RB", "RBR", "RBS", "RP", "SYM", "TO", "UH", "VB", "VBD", "VBG", "VBN", "VBP", "VBZ", "WDT", "WP", "WP$", "WRB"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}, "chunk_tags": {"feature": {"num_classes": 23, "names": ["O", "B-ADJP", "I-ADJP", "B-ADVP", "I-ADVP", "B-CONJP", "I-CONJP", "B-INTJ", "I-INTJ", "B-LST", "I-LST", "B-NP", "I-NP", "B-PP", "I-PP", "B-PRT", "I-PRT", "B-SBAR", "I-SBAR", "B-UCP", "I-UCP", "B-VP", "I-VP"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}, "ner_tags": {"feature": {"num_classes": 9, "names": ["O", "B-PER", "I-PER", "B-ORG", "I-ORG", "B-LOC", "I-LOC", "B-MISC", "I-MISC"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "conll2003", "config_name": "conll2003", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 6931393, "num_examples": 14041, "dataset_name": "conll2003"}, "validation": {"name": "validation", "num_bytes": 1739247, "num_examples": 3250, "dataset_name": "conll2003"}, "test": {"name": "test", "num_bytes": 1582078, "num_examples": 3453, "dataset_name": "conll2003"}}, "download_checksums": {"https://github.com/davidsbatista/NER-datasets/raw/master/CONLL2003/train.txt": {"num_bytes": 3283418, "checksum": "c99b26852dabf57ca9d30a0e892b84544cc8962003151e14a71077c55dc66db5"}, "https://github.com/davidsbatista/NER-datasets/raw/master/CONLL2003/valid.txt": {"num_bytes": 827441, "checksum": "f1f6469322876887de1d04acd43c59b02f59d5b02acf42c027132fa1bf349cb2"}, "https://github.com/davidsbatista/NER-datasets/raw/master/CONLL2003/test.txt": {"num_bytes": 748093, "checksum": "82e0c72d262f86ad3e78b15c5d980bbf87cb205aa4bf6d2d97643f463f8d7ff7"}}, "download_size": 4858952, "post_processing_size": null, "dataset_size": 10252718, "size_in_bytes": 15111670}}
+{"conll2003": {"description": "The shared task of CoNLL-2003 concerns language-independent named entity recognition. We will concentrate on\nfour types of named entities: persons, locations, organizations and names of miscellaneous entities that do\nnot belong to the previous three groups.\n\nThe CoNLL-2003 shared task data files contain four columns separated by a single space. Each word has been put on\na separate line and there is an empty line after each sentence. The first item on each line is a word, the second\na part-of-speech (POS) tag, the third a syntactic chunk tag and the fourth the named entity tag. The chunk tags\nand the named entity tags have the format I-TYPE which means that the word is inside a phrase of type TYPE. Only\nif two phrases of the same type immediately follow each other, the first word of the second phrase will have tag\nB-TYPE to show that it starts a new phrase. A word with tag O is not part of a phrase. Note the dataset uses IOB2\ntagging scheme, whereas the original dataset uses IOB1.\n\nFor more details see https://www.clips.uantwerpen.be/conll2003/ner/ and https://www.aclweb.org/anthology/W03-0419\n", "citation": "@inproceedings{tjong-kim-sang-de-meulder-2003-introduction,\n    title = \"Introduction to the {C}o{NLL}-2003 Shared Task: Language-Independent Named Entity Recognition\",\n    author = \"Tjong Kim Sang, Erik F.  and\n      De Meulder, Fien\",\n    booktitle = \"Proceedings of the Seventh Conference on Natural Language Learning at {HLT}-{NAACL} 2003\",\n    year = \"2003\",\n    url = \"https://www.aclweb.org/anthology/W03-0419\",\n    pages = \"142--147\",\n}\n", "homepage": "https://www.aclweb.org/anthology/W03-0419/", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "tokens": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "pos_tags": {"feature": {"num_classes": 47, "names": ["\"", "''", "#", "$", "(", ")", ",", ".", ":", "``", "CC", "CD", "DT", "EX", "FW", "IN", "JJ", "JJR", "JJS", "LS", "MD", "NN", "NNP", "NNPS", "NNS", "NN|SYM", "PDT", "POS", "PRP", "PRP$", "RB", "RBR", "RBS", "RP", "SYM", "TO", "UH", "VB", "VBD", "VBG", "VBN", "VBP", "VBZ", "WDT", "WP", "WP$", "WRB"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}, "chunk_tags": {"feature": {"num_classes": 23, "names": ["O", "B-ADJP", "I-ADJP", "B-ADVP", "I-ADVP", "B-CONJP", "I-CONJP", "B-INTJ", "I-INTJ", "B-LST", "I-LST", "B-NP", "I-NP", "B-PP", "I-PP", "B-PRT", "I-PRT", "B-SBAR", "I-SBAR", "B-UCP", "I-UCP", "B-VP", "I-VP"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}, "ner_tags": {"feature": {"num_classes": 9, "names": ["O", "B-PER", "I-PER", "B-ORG", "I-ORG", "B-LOC", "I-LOC", "B-MISC", "I-MISC"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "conll2003", "config_name": "conll2003", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 6931418, "num_examples": 14042, "dataset_name": "conll2003"}, "validation": {"name": "validation", "num_bytes": 1739271, "num_examples": 3251, "dataset_name": "conll2003"}, "test": {"name": "test", "num_bytes": 1582102, "num_examples": 3454, "dataset_name": "conll2003"}}, "download_checksums": {"https://data.deepai.org/conll2003.zip": {"num_bytes": 982975, "checksum": "96a104d174ddae7558bab603f19382c5fe02ff1da5c077a7f3ce2ced1578a2c3"}}, "download_size": 982975, "post_processing_size": null, "dataset_size": 10252791, "size_in_bytes": 11235766}}