Update files from the datasets library (from 1.1.3)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.1.3

dataset_infos.json

@@ -1 +1 @@
-{"germeval_14": {"description": "The GermEval 2014 NER Shared Task builds on a new dataset with German Named Entity annotation with the following properties:    - The data was sampled from German Wikipedia and News Corpora as a collection of citations.    - The dataset covers over 31,000 sentences corresponding to over 590,000 tokens.    - The NER annotation uses the NoSta-D guidelines, which extend the T\u00fcbingen Treebank guidelines,      using four main NER categories with sub-structure, and annotating embeddings among NEs      such as [ORG FC Kickers [LOC Darmstadt]].\n", "citation": "@inproceedings{benikova-etal-2014-nosta,\n    title = {NoSta-D Named Entity Annotation for German: Guidelines and Dataset},\n    author = {Benikova, Darina  and\n      Biemann, Chris  and\n      Reznicek, Marc},\n    booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation ({LREC}'14)},\n    month = {may},\n    year = {2014},\n    address = {Reykjavik, Iceland},\n    publisher = {European Language Resources Association (ELRA)},\n    url = {http://www.lrec-conf.org/proceedings/lrec2014/pdf/276_Paper.pdf},\n    pages = {2524--2531},\n}\n", "homepage": "https://sites.google.com/site/germeval2014ner/", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "source": {"dtype": "string", "id": null, "_type": "Value"}, "tokens": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "labels": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "nested-labels": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "germ_eval14", "config_name": "germeval_14", "version": {"version_str": "2.0.0", "description": null, "datasets_version_to_prepare": null, "major": 2, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 11305075, "num_examples": 24000, "dataset_name": "germ_eval14"}, "validation": {"name": "validation", "num_bytes": 1036186, "num_examples": 2200, "dataset_name": "germ_eval14"}, "test": {"name": "test", "num_bytes": 2407839, "num_examples": 5100, "dataset_name": "germ_eval14"}}, "download_checksums": {"https://drive.google.com/uc?export=download&id=1Jjhbal535VVz2ap4v4r_rN1UEHTdLK5P": {"num_bytes": 7882358, "checksum": "1e5a803d81f5fe6ade54700a7e8e9107a45edba80469d42e41a360550d1758e7"}, "https://drive.google.com/uc?export=download&id=1ZfRcQThdtAR5PPRjIDtrVP7BtXSCUBbm": {"num_bytes": 723876, "checksum": "d69d1347847e3ac0d1bfd14d7e5c0713dcb82899624301ced6df807dbb070056"}, "https://drive.google.com/uc?export=download&id=1u9mb7kNJHWQCWyweMDRMuTFoOHOfeBTH": {"num_bytes": 1682738, "checksum": "9405e49532379f3aee048851d116b35823d31c04e9521b87a9c4e6572c269097"}}, "download_size": 10288972, "post_processing_size": null, "dataset_size": 14749100, "size_in_bytes": 25038072}}
+{"germeval_14": {"description": "The GermEval 2014 NER Shared Task builds on a new dataset with German Named Entity annotation with the following properties:    - The data was sampled from German Wikipedia and News Corpora as a collection of citations.    - The dataset covers over 31,000 sentences corresponding to over 590,000 tokens.    - The NER annotation uses the NoSta-D guidelines, which extend the T\u00fcbingen Treebank guidelines,      using four main NER categories with sub-structure, and annotating embeddings among NEs      such as [ORG FC Kickers [LOC Darmstadt]].\n", "citation": "@inproceedings{benikova-etal-2014-nosta,\n    title = {NoSta-D Named Entity Annotation for German: Guidelines and Dataset},\n    author = {Benikova, Darina  and\n      Biemann, Chris  and\n      Reznicek, Marc},\n    booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation ({LREC}'14)},\n    month = {may},\n    year = {2014},\n    address = {Reykjavik, Iceland},\n    publisher = {European Language Resources Association (ELRA)},\n    url = {http://www.lrec-conf.org/proceedings/lrec2014/pdf/276_Paper.pdf},\n    pages = {2524--2531},\n}\n", "homepage": "https://sites.google.com/site/germeval2014ner/", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "source": {"dtype": "string", "id": null, "_type": "Value"}, "tokens": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner_tags": {"feature": {"num_classes": 25, "names": ["O", "B-LOC", "I-LOC", "B-LOCderiv", "I-LOCderiv", "B-LOCpart", "I-LOCpart", "B-ORG", "I-ORG", "B-ORGderiv", "I-ORGderiv", "B-ORGpart", "I-ORGpart", "B-OTH", "I-OTH", "B-OTHderiv", "I-OTHderiv", "B-OTHpart", "I-OTHpart", "B-PER", "I-PER", "B-PERderiv", "I-PERderiv", "B-PERpart", "I-PERpart"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}, "nested_ner_tags": {"feature": {"num_classes": 25, "names": ["O", "B-LOC", "I-LOC", "B-LOCderiv", "I-LOCderiv", "B-LOCpart", "I-LOCpart", "B-ORG", "I-ORG", "B-ORGderiv", "I-ORGderiv", "B-ORGpart", "I-ORGpart", "B-OTH", "I-OTH", "B-OTHderiv", "I-OTHderiv", "B-OTHpart", "I-OTHpart", "B-PER", "I-PER", "B-PERderiv", "I-PERderiv", "B-PERpart", "I-PERpart"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "germ_eval14", "config_name": "germeval_14", "version": {"version_str": "2.0.0", "description": null, "major": 2, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 13816714, "num_examples": 24000, "dataset_name": "germ_eval14"}, "validation": {"name": "validation", "num_bytes": 1266974, "num_examples": 2200, "dataset_name": "germ_eval14"}, "test": {"name": "test", "num_bytes": 2943201, "num_examples": 5100, "dataset_name": "germ_eval14"}}, "download_checksums": {"https://drive.google.com/uc?export=download&id=1Jjhbal535VVz2ap4v4r_rN1UEHTdLK5P": {"num_bytes": 7882358, "checksum": "1e5a803d81f5fe6ade54700a7e8e9107a45edba80469d42e41a360550d1758e7"}, "https://drive.google.com/uc?export=download&id=1ZfRcQThdtAR5PPRjIDtrVP7BtXSCUBbm": {"num_bytes": 723876, "checksum": "d69d1347847e3ac0d1bfd14d7e5c0713dcb82899624301ced6df807dbb070056"}, "https://drive.google.com/uc?export=download&id=1u9mb7kNJHWQCWyweMDRMuTFoOHOfeBTH": {"num_bytes": 1682738, "checksum": "9405e49532379f3aee048851d116b35823d31c04e9521b87a9c4e6572c269097"}}, "download_size": 10288972, "post_processing_size": null, "dataset_size": 18026889, "size_in_bytes": 28315861}}

germeval_14.py

@@ -85,8 +85,68 @@ class GermEval14(datasets.GeneratorBasedBuilder):
                     "id": datasets.Value("string"),
                     "source": datasets.Value("string"),
                     "tokens": datasets.Sequence(datasets.Value("string")),
-                    "labels": datasets.Sequence(datasets.Value("string")),
-                    "nested-labels": datasets.Sequence(datasets.Value("string")),
+                    "ner_tags": datasets.Sequence(
+                        datasets.features.ClassLabel(
+                            names=[
+                                "O",
+                                "B-LOC",
+                                "I-LOC",
+                                "B-LOCderiv",
+                                "I-LOCderiv",
+                                "B-LOCpart",
+                                "I-LOCpart",
+                                "B-ORG",
+                                "I-ORG",
+                                "B-ORGderiv",
+                                "I-ORGderiv",
+                                "B-ORGpart",
+                                "I-ORGpart",
+                                "B-OTH",
+                                "I-OTH",
+                                "B-OTHderiv",
+                                "I-OTHderiv",
+                                "B-OTHpart",
+                                "I-OTHpart",
+                                "B-PER",
+                                "I-PER",
+                                "B-PERderiv",
+                                "I-PERderiv",
+                                "B-PERpart",
+                                "I-PERpart",
+                            ]
+                        )
+                    ),
+                    "nested_ner_tags": datasets.Sequence(
+                        datasets.features.ClassLabel(
+                            names=[
+                                "O",
+                                "B-LOC",
+                                "I-LOC",
+                                "B-LOCderiv",
+                                "I-LOCderiv",
+                                "B-LOCpart",
+                                "I-LOCpart",
+                                "B-ORG",
+                                "I-ORG",
+                                "B-ORGderiv",
+                                "I-ORGderiv",
+                                "B-ORGpart",
+                                "I-ORGpart",
+                                "B-OTH",
+                                "I-OTH",
+                                "B-OTHderiv",
+                                "I-OTHderiv",
+                                "B-OTHpart",
+                                "I-OTHpart",
+                                "B-PER",
+                                "I-PER",
+                                "B-PERderiv",
+                                "I-PERderiv",
+                                "B-PERpart",
+                                "I-PERpart",
+                            ]
+                        )
+                    ),
                 }
             ),
             supervised_keys=None,
@@ -110,8 +170,8 @@ class GermEval14(datasets.GeneratorBasedBuilder):
             data = csv.reader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
             current_source = ""
             current_tokens = []
-            current_labels = []
-            current_nested_labels = []
+            current_ner_tags = []
+            current_nested_ner_tags = []
             sentence_counter = 0
             for row in data:
                 if row:
@@ -120,37 +180,39 @@ class GermEval14(datasets.GeneratorBasedBuilder):
                         continue
                     id_, token, label, nested_label = row[:4]
                     current_tokens.append(token)
-                    current_labels.append(label)
-                    current_nested_labels.append(nested_label)
+                    current_ner_tags.append(label)
+                    current_nested_ner_tags.append(nested_label)
                 else:
                     # New sentence
                     if not current_tokens:
                         # Consecutive empty lines will cause empty sentences
                         continue
-                    assert len(current_tokens) == len(current_labels), "💔 between len of tokens & labels"
-                    assert len(current_labels) == len(current_nested_labels), "💔 between len of labels & nested labels"
+                    assert len(current_tokens) == len(current_ner_tags), "💔 between len of tokens & labels"
+                    assert len(current_ner_tags) == len(
+                        current_nested_ner_tags
+                    ), "💔 between len of labels & nested labels"
                     assert current_source, "💥 Source for new sentence was not set"
                     sentence = (
                         sentence_counter,
                         {
                             "id": str(sentence_counter),
                             "tokens": current_tokens,
-                            "labels": current_labels,
-                            "nested-labels": current_nested_labels,
+                            "ner_tags": current_ner_tags,
+                            "nested_ner_tags": current_nested_ner_tags,
                             "source": current_source,
                         },
                     )
                     sentence_counter += 1
                     current_tokens = []
-                    current_labels = []
-                    current_nested_labels = []
+                    current_ner_tags = []
+                    current_nested_ner_tags = []
                     current_source = ""
                     yield sentence
             # Don't forget last sentence in dataset 🧐
             yield sentence_counter, {
                 "id": str(sentence_counter),
                 "tokens": current_tokens,
-                "labels": current_labels,
-                "nested-labels": current_nested_labels,
+                "ner_tags": current_ner_tags,
+                "nested_ner_tags": current_nested_ner_tags,
                 "source": current_source,
             }