Ebiquity V2 dataset added.

dataset_infos.json

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+{"ebiquity-v2": {"description": "\nEbiquity V2 (non-stemmed) dataset for Nepali NER task. The dataset is tagged with BIO scheme.\n", "citation": "\n@INPROCEEDINGS{\n  8998477,\n  author={O. M. {Singh} and A. {Padia} and A. {Joshi}},\n  booktitle={2019 IEEE 5th International Conference on Collaboration and Internet Computing (CIC)},\n  title={Named Entity Recognition for Nepali Language},\n  year={2019},\n  volume={},\n  number={},\n  pages={184-190},\n  keywords={Named Entity Recognition;Nepali;Low-resource;BiLSTM;CNN;Grapheme},\n  doi={10.1109/CIC48465.2019.00031},\n  ISSN={null},\n  month={Dec},}\n", "homepage": "https://arxiv.org/abs/1908.05828", "license": "", "features": {"id": {"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": 9, "names": ["O", "B-PER", "I-PER", "B-ORG", "I-ORG", "B-LOC", "I-LOC", "B-MISC", "I-MISC"], "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "ebiquity_v2", "config_name": "ebiquity-v2", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2034448, "num_examples": 3289, "dataset_name": "ebiquity_v2"}}, "download_checksums": {"https://raw.githubusercontent.com/oya163/nepali-ner/master/data/ebiquity_v2/raw/total.bio": {"num_bytes": 1450701, "checksum": "05b16ee0c99706ddb278628f46516ac9d373787a39967484eb28eab4a12875c6"}}, "download_size": 1450701, "post_processing_size": null, "dataset_size": 2034448, "size_in_bytes": 3485149}}

ebiquity-v2.py

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+import re
+
+import datasets
+
+_CITATION = """
+@INPROCEEDINGS{
+  8998477,
+  author={O. M. {Singh} and A. {Padia} and A. {Joshi}},
+  booktitle={2019 IEEE 5th International Conference on Collaboration and Internet Computing (CIC)},
+  title={Named Entity Recognition for Nepali Language},
+  year={2019},
+  volume={},
+  number={},
+  pages={184-190},
+  keywords={Named Entity Recognition;Nepali;Low-resource;BiLSTM;CNN;Grapheme},
+  doi={10.1109/CIC48465.2019.00031},
+  ISSN={null},
+  month={Dec},}
+"""
+
+_DESCRIPTION = """
+Ebiquity V2 (non-stemmed) dataset for Nepali NER task. The dataset is tagged with BIO scheme.
+"""
+
+_URL = "https://raw.githubusercontent.com/oya163/nepali-ner/master/data/ebiquity_v2/raw/total.bio"
+
+
+class EbiquityV2Config(datasets.BuilderConfig):
+  """BuilderConfig for Conll2003"""
+  
+  def __init__(self, **kwargs):
+    """BuilderConfig for Ebiquity V2.
+    Args:
+      **kwargs: keyword arguments forwarded to super.
+    """
+    super(EbiquityV2Config, self).__init__(**kwargs)
+
+
+class EbiquityV2(datasets.GeneratorBasedBuilder):
+  """Ebiquity V2"""
+  
+  BUILDER_CONFIGS = [
+    EbiquityV2Config(name="ebiquity-v2", version=datasets.Version("1.0.0"), description="Ebiquity V2 dataset"),
+  ]
+  
+  def _info(self):
+    return datasets.DatasetInfo(
+      description=_DESCRIPTION,
+      features=datasets.Features(
+        {
+          "id": datasets.Value("string"),
+          "tokens": datasets.Sequence(datasets.Value("string")),
+          "ner_tags": datasets.Sequence(
+            datasets.features.ClassLabel(
+              names=[
+                "O",
+                "B-PER",
+                "I-PER",
+                "B-ORG",
+                "I-ORG",
+                "B-LOC",
+                "I-LOC",
+                "B-MISC",
+                "I-MISC",
+              ]
+            )
+          ),
+        }
+      ),
+      supervised_keys=None,
+      homepage="https://arxiv.org/abs/1908.05828",
+      citation=_CITATION,
+    )
+    
+  def _split_generators(self, dl_manager):
+    downloaded_file = dl_manager.download_and_extract(_URL)
+    return [
+      datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_file})
+    ]
+  
+  def _generate_examples(self, filepath):
+    with open(filepath, encoding="utf-8") as f:
+      guid = 0
+      tokens = []
+      ner_tags = []
+      for line in f:
+        if line == "" or line == "\n":
+          if tokens:
+            yield guid, {
+              "id": str(guid),
+              "tokens": tokens,
+              "ner_tags": ner_tags,
+            }
+            guid += 1
+            tokens = []
+            ner_tags = []
+        else:
+          splits = re.split('\t+', line)
+          tokens.append(splits[0])
+          ner_tags.append(splits[1].rstrip())
+      yield guid, {
+        "id": str(guid),
+        "tokens": tokens,
+        "ner_tags": ner_tags,
+      }