Upload wikiner-es.py

wikiner-es.py

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+# coding=utf-8
+# Copyright 2020 HuggingFace Datasets Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import logging
+
+import datasets
+
+
+_CITATION = """\
+@inproceedings{,
+    title = "",
+    author = "Garagiola, Nazareno",
+    year = "2022",
+    url = ""
+}
+"""
+
+_DESCRIPTION = """Dataset used to train a NER model"""
+_URL = "https://raw.githubusercontent.com/NazaGara/betoNER/main/data/wikiner/"
+_TRAINING_FILE = "train.conllu"
+
+
+class WikinerConfig(datasets.BuilderConfig):
+    """BuilderConfig"""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(WikinerConfig, self).__init__(**kwargs)
+
+
+class Wikiner(datasets.GeneratorBasedBuilder):
+    """Wikiner dataset."""
+
+    BUILDER_CONFIGS = [
+        WikinerConfig(
+            name="wikiner",
+            version=datasets.Version("1.1.0"),
+            description="wikiner dataset",
+        ),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "tokens": datasets.Sequence(datasets.Value("string")),
+                    "pos_tags": datasets.Sequence(
+                        datasets.features.ClassLabel(
+                            names=[
+                                "ACRNM",
+                                "ADJ",
+                                "ADV",
+                                "ALFS",
+                                "ART",
+                                "BACKSLASH",
+                                "CARD",
+                                "CC",
+                                "CCAD",
+                                "CCNEG",
+                                "CM",
+                                "CODE",
+                                "COLON",
+                                "CQUE",
+                                "CSUBF",
+                                "CSUBI",
+                                "CSUBX",
+                                "DM",
+                                "DOTS",
+                                "FS",
+                                "INT",
+                                "LP",
+                                "NC",
+                                "NEG",
+                                "NMEA",
+                                "NMON",
+                                "NP",
+                                "ORD",
+                                "PAL",
+                                "PDEL",
+                                "PE",
+                                "PERCT",
+                                "PPC",
+                                "PPO",
+                                "PPX",
+                                "PREP",
+                                "QT",
+                                "QU",
+                                "REL",
+                                "RP",
+                                "SE",
+                                "SEMICOLON",
+                                "SLASH",
+                                "SYM",
+                                "UMMX",
+                                "VCLIfin",
+                                "VCLIger",
+                                "VCLIinf",
+                                "VEadj",
+                                "VEfin",
+                                "VEger",
+                                "VEinf",
+                                "VHadj",
+                                "VHfin",
+                                "VHger",
+                                "VHinf",
+                                "VLadj",
+                                "VLfin",
+                                "VLger",
+                                "VLinf",
+                                "VMadj",
+                                "VMfin",
+                                "VMger",
+                                "VMinf",
+                                "VSadj",
+                                "VSfin",
+                                "VSger",
+                                "VSinf",
+                            ]
+                        )
+                    ),
+                    "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=_URL,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        urls_to_download = {
+            "train": f"{_URL}{_TRAINING_FILE}",
+        }
+        downloaded_files = dl_manager.download_and_extract(urls_to_download)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": downloaded_files["train"]},
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        logging.info("⏳ Generating examples from = %s", filepath)
+        with open(filepath, encoding="utf-8") as f:
+            guid = 0
+            tokens = []
+            pos_tags = []
+            ner_tags = []
+            for line in f:
+                if line.startswith("-DOCSTART-") or line == "" or line == "\n":
+                    if tokens:
+                        yield guid, {
+                            "id": str(guid),
+                            "tokens": tokens,
+                            "pos_tags": pos_tags,
+                            "ner_tags": ner_tags,
+                        }
+                        guid += 1
+                        tokens = []
+                        pos_tags = []
+                        ner_tags = []
+                else:
+                    splits = line.split(" ")
+                    tokens.append(splits[0])
+                    pos_tags.append(splits[1])
+                    ner_tags.append(splits[2].rstrip())
+            # last example
+            if tokens:
+                yield guid, {
+                    "id": str(guid),
+                    "tokens": tokens,
+                    "pos_tags": pos_tags,
+                    "ner_tags": ner_tags,
+                }