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README.md

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----
-license: cc-by-sa-4.0
----

SDU-test.py

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-import os
-
-import datasets
-from typing import List
-import json
-
-logger = datasets.logging.get_logger(__name__)
-
-
-_CITATION = """
-"""
-
-_DESCRIPTION = """
-This is the dataset repository for SDU Dataset from SDU workshop at AAAI22.
-The dataset can help build sequence labelling models for the task Abbreviation Detection.
-"""
-
-class SDUtestConfig(datasets.BuilderConfig):
-    """BuilderConfig for Conll2003"""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig forConll2003.
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(SDUtestConfig, self).__init__(**kwargs)
-
-
-class SDUtestConfig(datasets.GeneratorBasedBuilder):
-    """SDU Filtered dataset."""
-
-    BUILDER_CONFIGS = [
-        SDUtestConfig(name="SDUtest", version=datasets.Version("0.0.2"), description="SDU test 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=[
-                                "B-O",
-                                "B-AC",
-                                "I-AC",
-                                "B-LF",
-                                "I-LF"
-                            ]
-                        )
-                    ),
-                }
-            ),
-            supervised_keys=None,
-            homepage="",
-            citation=_CITATION,
-        )
-
-    _URL = "https://huggingface.co/datasets/surrey-nlp/SDU-test/raw/main/"
-    _URLS = {
-        "train+dev": _URL + "sdu_data_trunc.json",
-        #"dev": _URL + "PLOS-val15-filtered-pos_bio.json",
-        #"test": _URL + "PLOS-test15-filtered-pos_bio.json"
-    }
-
-    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
-        urls_to_download = self._URLS
-        downloaded_files = dl_manager.download_and_extract(urls_to_download)
-
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train+dev"]}),
-            #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):
-        """This function returns the examples in the raw (text) form."""
-        logger.info("generating examples from = %s", filepath)
-        with open(filepath) as f:
-            plod = json.load(f)
-            for object in plod:
-                id_ = int(object['id'])
-                yield id_, {
-                    "id": str(id_),
-                    "tokens": object['tokens'],
-                    #"pos_tags": object['pos_tags'],
-                    "ner_tags": object['ner_tags'],
-                }

SDUtest/sdu-test-train.parquet

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