Update parquet files

selfkg-dwy100k-dbpyg.zip → pairs/selfkg-dwy100k-dbpyg-ref.parquet

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pairs/selfkg-dwy100k-dbpyg-valid.parquet

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selfkg-dwy100k-dbpyg.py

@@ -1,196 +0,0 @@
-import json
-import os
-import pickle
-
-import datasets
-
-logger = datasets.logging.get_logger(__name__)
-
-# _SUBFIELD = "yg"
-
-# _VERSION = "1.0.0"
-
-# _DESCRIPTION = """\
-#     DWY100k-yg is a large-scale monolingual dataset extracted from DBpedia and YAGO3. The suffix yg means DBpedia 
-#     to YAGO3. And DWY100k-yg has 100,000 reference entity alignments.
-# """
-
-# _CITATION = """\
-#     @inproceedings{sun2018bootstrapping,
-#     title={Bootstrapping Entity Alignment with Knowledge Graph Embedding.},
-#     author={Sun, Zequn and Hu, Wei and Zhang, Qingheng and Qu, Yuzhong},
-#     booktitle={IJCAI},
-#     volume={18},
-#     pages={4396--4402},
-#     year={2018}
-# }
-# """
-
-# _URL = "https://dl.acm.org/doi/10.1145/3485447.3511945"
-
-# _PREFIX = "https://huggingface.co/datasets/matchbench/selfkg-dwy100k-dbpyg"
-
-# _URLS = {
-#     "source": f"{_PREFIX}/resolve/main/selfkg-dwy100k-dbp{_SUBFIELD}-src.zip",
-#     "target": f"{_PREFIX}/resolve/main/selfkg-dwy100k-dbp{_SUBFIELD}-tgt.zip",
-#     "pairs": f"{_PREFIX}/resolve/main/selfkg-dwy100k-dbp{_SUBFIELD}-pairs.zip",
-# }
-
-class SelfkgDwy100kygConfig(datasets.BuilderConfig):
-    """BuilderConfig for Selfkg-DWY100k."""
-
-    def __init__(self, features, data_url, citation, url, label_classes=("False", "True"), **kwargs):
-        """
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(SelfkgDwy100kygConfig, self).__init__(**kwargs)
-        self.features = features
-        self.label_classes = label_classes
-        self.data_url = data_url
-        self.citation = citation
-        self.url = url
-
-class DWY100kYg(datasets.GeneratorBasedBuilder):
-    """DWY100k-yg: A Entity Alignment Dataset. From DBpedia to YAGO3."""
-
-    BUILDER_CONFIGS = [
-        SelfkgDwy100kygConfig(
-            name="source",
-            features=["column1", "column2", "column3"],
-            citation="TODO",
-            url="TODO",
-            data_url="https://huggingface.co/datasets/matchbench/selfkg-dwy100k-dbpyg/resolve/main/selfkg-dwy100k-dbpyg.zip"
-        ),
-        SelfkgDwy100kygConfig(
-            name="target",
-            features=["column1", "column2", "column3"],
-            citation="TODO",
-            url="TODO",
-            data_url="https://huggingface.co/datasets/matchbench/selfkg-dwy100k-dbpyg/resolve/main/selfkg-dwy100k-dbpyg.zip"
-        ),
-        SelfkgDwy100kygConfig(
-            name="pairs",
-            features=["left_id","right_id"],
-            citation="TODO",
-            url="TODO",
-            data_url="https://huggingface.co/datasets/matchbench/selfkg-dwy100k-dbpyg/resolve/main/selfkg-dwy100k-dbpyg.zip"
-        ),
-    ]
-
-    def _info(self) -> datasets.DatasetInfo:
-        if self.config.name=="source":
-            features = {feature: datasets.Value("string") for feature in self.config.features}
-        elif self.config.name=="target":
-            features = {feature: datasets.Value("string") for feature in self.config.features}
-        elif self.config.name=="pairs":
-            features = {feature: datasets.Value("int32") for feature in self.config.features}
-        
-        return datasets.DatasetInfo(features = datasets.Features(features))
-
-
-    def _split_generators(self, dl_manager):
-
-        dl_dir = dl_manager.download_and_extract(self.config.data_url) or ""
-        if self.config.name == "source":
-            return [
-            datasets.SplitGenerator(
-                name="ent_ids",
-                gen_kwargs={
-                    "data_file": os.path.join(dl_dir, "id_ent_1"),
-                    "split": "ent_ids",
-                },
-            ),
-            datasets.SplitGenerator(
-                name="rel_triples_id",
-                gen_kwargs={
-                    "data_file": os.path.join(dl_dir, "triples_1"),
-                    "split": "rel_triples_id",
-                },
-            ),
-            datasets.SplitGenerator(
-                name="LaBSE_emb",
-                gen_kwargs={
-                    "data_file": os.path.join(dl_dir, "raw_LaBSE_emb_1.pkl"),
-                    "split": "LaBSE_emb",
-                },
-            ),
-            ]
-        elif self.config.name == "target":
-            return [
-            datasets.SplitGenerator(
-                name="ent_ids",
-                gen_kwargs={
-                    "data_file": os.path.join(dl_dir, "id_ent_2"),
-                    "split": "ent_ids",
-                },
-            ),
-            datasets.SplitGenerator(
-                name="rel_triples_id",
-                gen_kwargs={
-                    "data_file": os.path.join(dl_dir, "triples_2"),
-                    "split": "rel_triples_id",
-                },
-            ),
-            datasets.SplitGenerator(
-                name="LaBSE_emb",
-                gen_kwargs={
-                    "data_file": os.path.join(dl_dir, "raw_LaBSE_emb_2.pkl"),
-                    "split": "LaBSE_emb",
-                },
-            ),
-            ]
-        elif self.config.name == "pairs":
-            return [
-            datasets.SplitGenerator(
-                name="ref",
-                gen_kwargs={
-                    "data_file": os.path.join(dl_dir, "ref_ent_ids"),
-                    "split": "ref",
-                },
-            ),
-            datasets.SplitGenerator(
-                name="valid",
-                gen_kwargs={
-                    "data_file": os.path.join(dl_dir, "valid.ref"),
-                    "split": "valid",
-                },
-            ),
-            ]
-        
-    def _generate_examples(self, data_file, split):
-        if split in ["LaBSE_emb"]:
-            des = pickle.load(open(data_file,"rb"))
-            i = -1
-            for ent_ids,ori_emb in des.items():
-                i += 1
-                yield i, {
-                    "column1": ent_ids,
-                    "column2": ori_emb,
-                    "column3": None
-                }
-        else:    
-            f = open(data_file,"r", encoding='utf-8')
-            data = f.readlines()
-            for i in range(len(data)):
-                if self.config.name in ["source", "target"]:
-                    if split in ["ent_ids"]:
-                        row = data[i].strip('\n').split('\t')
-                        yield i, {
-                                    "column1": row[0],
-                                    "column2": row[1],
-                                    "column3": None
-                                }
-                    elif split in ["rel_triples_id"]:
-                        row = data[i].strip('\n').split('\t')
-                        yield i, {
-                                    "column1": row[0],
-                                    "column2": row[1],
-                                    "column3": row[2]
-                                }
-                if self.config.name == "pairs":
-                    row = data[i].strip('\n').split('\t')
-                    yield i, {
-                                "left_id": row[0],
-                                "right_id": row[1]
-                    }

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