upload the first config

README.md

@@ -1,17 +1,102 @@
 ---
+language:
+- kk
 license: cc-by-4.0
 multilinguality:
 - monolingual
+size_categories:
+- 100K<n<1M
 task_categories:
 - token-classification
 task_ids:
 - named-entity-recognition
-language:
-- kk
 pretty_name: A Named Entity Recognition Dataset for Kazakh
-size_categories:
-- 100K<n<1M
 viewer: true
+dataset_info:
+  config_name: ner_kazakh
+  features:
+  - name: index
+    dtype: string
+  - name: sentence_id
+    dtype: string
+  - name: tokens
+    sequence: string
+  - name: ner_tags
+    sequence:
+      class_label:
+        names:
+          '0': O
+          '1': B-ADAGE
+          '2': I-ADAGE
+          '3': B-ART
+          '4': I-ART
+          '5': B-CARDINAL
+          '6': I-CARDINAL
+          '7': B-CONTACT
+          '8': I-CONTACT
+          '9': B-DATE
+          '10': I-DATE
+          '11': B-DISEASE
+          '12': I-DISEASE
+          '13': B-EVENT
+          '14': I-EVENT
+          '15': B-FACILITY
+          '16': I-FACILITY
+          '17': B-GPE
+          '18': I-GPE
+          '19': B-LANGUAGE
+          '20': I-LANGUAGE
+          '21': B-LAW
+          '22': I-LAW
+          '23': B-LOCATION
+          '24': I-LOCATION
+          '25': B-MISCELLANEOUS
+          '26': I-MISCELLANEOUS
+          '27': B-MONEY
+          '28': I-MONEY
+          '29': B-NON_HUMAN
+          '30': I-NON_HUMAN
+          '31': B-NORP
+          '32': I-NORP
+          '33': B-ORDINAL
+          '34': I-ORDINAL
+          '35': B-ORGANISATION
+          '36': I-ORGANISATION
+          '37': B-PERSON
+          '38': I-PERSON
+          '39': B-PERCENTAGE
+          '40': I-PERCENTAGE
+          '41': B-POSITION
+          '42': I-POSITION
+          '43': B-PRODUCT
+          '44': I-PRODUCT
+          '45': B-PROJECT
+          '46': I-PROJECT
+          '47': B-QUANTITY
+          '48': I-QUANTITY
+          '49': B-TIME
+          '50': I-TIME
+  splits:
+  - name: train
+    num_bytes: 26219395
+    num_examples: 88540
+  - name: validation
+    num_bytes: 3268409
+    num_examples: 11067
+  - name: test
+    num_bytes: 3252196
+    num_examples: 11068
+  download_size: 9016377
+  dataset_size: 32740000
+configs:
+- config_name: ner_kazakh
+  data_files:
+  - split: train
+    path: ner_kazakh/train-*
+  - split: validation
+    path: ner_kazakh/validation-*
+  - split: test
+    path: ner_kazakh/test-*
 ---
 # A Named Entity Recognition Dataset for Kazakh
 - This is a modified version of the dataset provided in the [LREC 2022](https://lrec2022.lrec-conf.org/en/) paper [*KazNERD: Kazakh Named Entity Recognition Dataset*](https://aclanthology.org/2022.lrec-1.44).

ner-kazakh.py

@@ -1,158 +0,0 @@
-"""ner_kazakh"""
-
-import os
-import re
-
-import datasets
-
-logger = datasets.logging.get_logger(__name__)
-
-_CITATION = """\
-"""
-
-_DESCRIPTION = "ner_kazakh"
-_URL = "./"
-_TRAINING_FILE = "ner_kazakh_train.txt"
-_DEV_FILE = "ner_kazakh_valid.txt"
-_TEST_FILE = "ner_kazakh_test.txt"
-
-class ner_kazakhConfig(datasets.BuilderConfig):
-	"""BuilderConfig for ner_kazakh"""
-
-	def __init__(self, **kwargs):
-		"""BuilderConfig for ner_kazakh.
-		Args:
-		  **kwargs: keyword arguments forwarded to super.
-		"""
-		super(ner_kazakhConfig, self).__init__(**kwargs)
-
-class ner_kazakh(datasets.GeneratorBasedBuilder):
-	"""ner_kazakh dataset."""
-
-	BUILDER_CONFIGS = [
-		ner_kazakhConfig(name = "ner_kazakh", version = datasets.Version("1.0.0"), description = "ner_kazakh"),
-	]
-
-	def _info(self):
-		return datasets.DatasetInfo(
-			description =_DESCRIPTION,
-			features = datasets.Features(
-				{
-					"index": datasets.Value("string"),
-					"sentence_id": datasets.Value("string"),
-					"tokens": datasets.Sequence(datasets.Value("string")),
-					"ner_tags": datasets.Sequence(
-						datasets.features.ClassLabel(
-							names = [
-								"O",
-								"B-ADAGE",
-								"I-ADAGE",
-								"B-ART",
-								"I-ART",
-								"B-CARDINAL",
-								"I-CARDINAL",
-								"B-CONTACT",
-								"I-CONTACT",
-								"B-DATE",
-								"I-DATE",
-								"B-DISEASE",
-								"I-DISEASE",
-								"B-EVENT",
-								"I-EVENT",
-								"B-FACILITY",
-								"I-FACILITY",
-								"B-GPE",
-								"I-GPE",
-								"B-LANGUAGE",
-								"I-LANGUAGE",
-								"B-LAW",
-								"I-LAW",
-								"B-LOCATION",
-								"I-LOCATION",
-								"B-MISCELLANEOUS",
-								"I-MISCELLANEOUS",
-								"B-MONEY",
-								"I-MONEY",
-								"B-NON_HUMAN",
-								"I-NON_HUMAN",
-								"B-NORP",
-								"I-NORP",
-								"B-ORDINAL",
-								"I-ORDINAL",
-								"B-ORGANISATION",
-								"I-ORGANISATION",
-								"B-PERSON",
-								"I-PERSON",
-								"B-PERCENTAGE",
-								"I-PERCENTAGE",
-								"B-POSITION",
-								"I-POSITION",
-								"B-PRODUCT",
-								"I-PRODUCT",
-								"B-PROJECT",
-								"I-PROJECT",
-								"B-QUANTITY",
-								"I-QUANTITY",
-								"B-TIME",
-								"I-TIME",
-							]
-						)
-					),
-				}
-			),
-			supervised_keys = None,
-			homepage = "",
-			citation = _CITATION,
-		)
-
-	def _split_generators(self, dl_manager):
-		"""Returns SplitGenerators."""
-		data_files = {
-			"train": f"{_URL}{_TRAINING_FILE}",
-			"dev": f"{_URL}{_DEV_FILE}",
-			"test": f"{_URL}{_TEST_FILE}",
-		}
-		downloaded_files = dl_manager.download_and_extract(data_files)
-
-		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"]}),
-		]
-
-	def _generate_examples(self, filepath):
-		logger.info("⏳ Generating examples from = %s", filepath)
-		with open(filepath, encoding="utf-8") as f:
-			index = 0
-			sent_ids = []
-			tokens = []
-			ner_tags = []
-			for line in f:
-				if line.startswith("-DOCSTART-") or line == "" or line == "\n":
-					if tokens:
-						yield index, {
-							"index": str(index),
-							"sentence_id": sent_ids,
-							"tokens": tokens,
-							"ner_tags": ner_tags,
-						}
-						index += 1
-						sent_ids = []
-						tokens = []
-						ner_tags = []
-				else:
-					# ner_kazakh tokens are space separated
-					splits = line.split(" ")
-					if re.match(r"[A-Z]{3}\d{6}[A-Z]{3}", line):
-						sent_ids.append(splits[0])
-					else:
-						tokens.append(splits[0])
-						ner_tags.append(splits[1].rstrip())
-			# last example
-			if tokens:
-				yield index, {
-					"index": str(index),
-					"sentence_id": sent_ids,
-					"tokens": tokens,
-					"ner_tags": ner_tags,
-				}

ner_kazakh/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:045fc74f82eeff1a60b77696945d2692dd0a4e594465dd683cfacb2614001ce7
+size 903618

ner_kazakh/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d61e2d7810fd56ce65deccfdc4e0f15661f8f9482a5c19cbccdb548569bb4a5e
+size 7209684

ner_kazakh/validation-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1cb639a20c4858eb3c84094d5fd04c3133fa79f9b9e8d274f518517d9c6bb582
+size 903075