Update README and dataset_infos.json

README.md

@@ -21,11 +21,18 @@ task_ids:
 - part-of-speech
 paperswithcode_id: conll-2002
 pretty_name: CoNLL-2002
+config_names:
+- es
+- nl
 dataset_info:
 - config_name: es
   features:
   - name: id
     dtype: string
+  - name: document_id
+    dtype: int32
+  - name: sentence_id
+    dtype: int32
   - name: tokens
     sequence: string
   - name: pos_tags
@@ -107,20 +114,24 @@ dataset_info:
           '8': I-MISC
   splits:
   - name: train
-    num_bytes: 6672173
-    num_examples: 8324
+    num_bytes: 6738717
+    num_examples: 8323
   - name: validation
-    num_bytes: 1333784
-    num_examples: 1916
+    num_bytes: 1349064
+    num_examples: 1915
   - name: test
-    num_bytes: 1294156
-    num_examples: 1518
+    num_bytes: 1306252
+    num_examples: 1517
   download_size: 4140690
-  dataset_size: 9300113
+  dataset_size: 9394033
 - config_name: nl
   features:
   - name: id
     dtype: string
+  - name: document_id
+    dtype: int32
+  - name: sentence_id
+    dtype: int32
   - name: tokens
     sequence: string
   - name: pos_tags
@@ -154,19 +165,16 @@ dataset_info:
           '8': I-MISC
   splits:
   - name: train
-    num_bytes: 5308959
-    num_examples: 15807
+    num_bytes: 5435346
+    num_examples: 15806
   - name: validation
-    num_bytes: 994298
-    num_examples: 2896
+    num_bytes: 1017418
+    num_examples: 2895
   - name: test
-    num_bytes: 1808862
-    num_examples: 5196
+    num_bytes: 1850382
+    num_examples: 5195
   download_size: 3642241
-  dataset_size: 8112119
-config_names:
-- es
-- nl
+  dataset_size: 8303146
 ---
 
 # Dataset Card for CoNLL-2002

dataset_infos.json

@@ -1 +1 @@
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co-training).\n\nThe train/validation/test sets are available in Spanish and Dutch.\n\nFor more details see https://www.clips.uantwerpen.be/conll2002/ner/ and https://www.aclweb.org/anthology/W02-2024/\n", "citation": "@inproceedings{tjong-kim-sang-2002-introduction,\n    title = \"Introduction to the {C}o{NLL}-2002 Shared Task: Language-Independent Named Entity Recognition\",\n    author = \"Tjong Kim Sang, Erik F.\",\n    booktitle = \"{COLING}-02: The 6th Conference on Natural Language Learning 2002 ({C}o{NLL}-2002)\",\n    year = \"2002\",\n    url = \"https://www.aclweb.org/anthology/W02-2024\",\n}\n", "homepage": "https://www.aclweb.org/anthology/W02-2024/", "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": 60, "names": ["AO", "AQ", "CC", "CS", "DA", "DE", "DD", "DI", "DN", "DP", "DT", 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locations, times and quantities.\n\nExample:\n[PER Wolff] , currently a journalist in [LOC Argentina] , played with [PER Del Bosque] in the final years of the seventies in [ORG Real Madrid] .\n\nThe shared task of CoNLL-2002 concerns language-independent named entity recognition.\nWe will concentrate on four types of named entities: persons, locations, organizations and names of miscellaneous entities that do not belong to the previous three groups.\nThe participants of the shared task will be offered training and test data for at least two languages.\nThey will use the data for developing a named-entity recognition system that includes a machine learning component.\nInformation sources other than the training data may be used in this shared task.\nWe are especially interested in methods that can use additional unannotated data for improving their performance (for example co-training).\n\nThe train/validation/test sets are available in Spanish and Dutch.\n\nFor more details see https://www.clips.uantwerpen.be/conll2002/ner/ and https://www.aclweb.org/anthology/W02-2024/\n", "citation": "@inproceedings{tjong-kim-sang-2002-introduction,\n    title = \"Introduction to the {C}o{NLL}-2002 Shared Task: Language-Independent Named Entity Recognition\",\n    author = \"Tjong Kim Sang, Erik F.\",\n    booktitle = \"{COLING}-02: The 6th Conference on Natural Language Learning 2002 ({C}o{NLL}-2002)\",\n    year = \"2002\",\n    url = \"https://www.aclweb.org/anthology/W02-2024\",\n}\n", "homepage": "https://www.aclweb.org/anthology/W02-2024/", "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": 12, "names": ["Adj", "Adv", "Art", "Conj", "Int", "Misc", "N", "Num", "Prep", "Pron", "Punc", "V"], "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": "conll2002", "config_name": "nl", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 5308959, "num_examples": 15807, "dataset_name": "conll2002"}, "validation": {"name": "validation", "num_bytes": 994298, "num_examples": 2896, "dataset_name": "conll2002"}, "test": {"name": "test", "num_bytes": 1808862, "num_examples": 5196, "dataset_name": "conll2002"}}, "download_checksums": {"https://raw.githubusercontent.com/teropa/nlp/master/resources/corpora/conll2002/ned.train": {"num_bytes": 2377174, "checksum": "0a419dcb356b62c8cff38515675550b3d5dbea9f45a1c4956328dbd5cc7fcdbc"}, 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+{"es": {"description": "Named entities are phrases that contain the names of persons, organizations, locations, times and quantities.\n\nExample:\n[PER Wolff] , currently a journalist in [LOC Argentina] , played with [PER Del Bosque] in the final years of the seventies in [ORG Real Madrid] .\n\nThe shared task of CoNLL-2002 concerns language-independent named entity recognition.\nWe will concentrate on four types of named entities: persons, locations, organizations and names of miscellaneous entities that do not belong to the previous three groups.\nThe participants of the shared task will be offered training and test data for at least two languages.\nThey will use the data for developing a named-entity recognition system that includes a machine learning component.\nInformation sources other than the training data may be used in this shared task.\nWe are especially interested in methods that can use additional unannotated data for improving their performance (for example co-training).\n\nThe train/validation/test sets are available in Spanish and Dutch.\n\nFor more details see https://www.clips.uantwerpen.be/conll2002/ner/ and https://www.aclweb.org/anthology/W02-2024/\n", "citation": "@inproceedings{tjong-kim-sang-2002-introduction,\n    title = \"Introduction to the {C}o{NLL}-2002 Shared Task: Language-Independent Named Entity Recognition\",\n    author = \"Tjong Kim Sang, Erik F.\",\n    booktitle = \"{COLING}-02: The 6th Conference on Natural Language Learning 2002 ({C}o{NLL}-2002)\",\n    year = \"2002\",\n    url = \"https://www.aclweb.org/anthology/W02-2024\",\n}\n", "homepage": "https://www.aclweb.org/anthology/W02-2024/", "license": "", "features": {"id": {"dtype": "string", "_type": "Value"}, "document_id": {"dtype": "int32", "_type": "Value"}, "sentence_id": {"dtype": "int32", "_type": "Value"}, "tokens": {"feature": {"dtype": "string", "_type": "Value"}, "_type": "Sequence"}, "pos_tags": {"feature": {"names": ["AO", "AQ", "CC", "CS", "DA", 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names of persons, organizations, locations, times and quantities.\n\nExample:\n[PER Wolff] , currently a journalist in [LOC Argentina] , played with [PER Del Bosque] in the final years of the seventies in [ORG Real Madrid] .\n\nThe shared task of CoNLL-2002 concerns language-independent named entity recognition.\nWe will concentrate on four types of named entities: persons, locations, organizations and names of miscellaneous entities that do not belong to the previous three groups.\nThe participants of the shared task will be offered training and test data for at least two languages.\nThey will use the data for developing a named-entity recognition system that includes a machine learning component.\nInformation sources other than the training data may be used in this shared task.\nWe are especially interested in methods that can use additional unannotated data for improving their performance (for example co-training).\n\nThe train/validation/test sets are available in Spanish and 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