Create Hansel.py

Hansel.py

@@ -0,0 +1,171 @@
+# coding=utf-8
+
+"""Hansel: A Chinese Few-Shot and Zero-Shot Entity Linking Benchmark"""
+
+
+import json
+import os
+
+import datasets
+
+
+
+_HANSEL_CITATION = """\
+@misc{xu2022hansel,
+  title = {Hansel: A Chinese Few-Shot and Zero-Shot Entity Linking Benchmark},
+  author = {Xu, Zhenran and Shan, Zifei and Li, Yuxin and Hu, Baotian and Qin, Bing},
+  publisher = {arXiv},
+  year = {2022},
+  url = {https://arxiv.org/abs/2207.13005}
+}
+
+"""
+
+_HANSEL_DESCRIPTION = """\
+Hansel is a high-quality human-annotated Chinese entity linking (EL) dataset, used for testing Chinese EL systems' generalization ability to tail entities and emerging entities.
+The test set contains Few-shot (FS) and zero-shot (ZS) slices, has 10K examples and uses Wikidata as the corresponding knowledge base.
+The training and validation sets are from Wikipedia hyperlinks, useful for large-scale pretraining of Chinese EL systems.
+
+"""
+
+
+_URLS = {
+    "train": "hansel-train.jsonl",
+    "val": "hansel-val.jsonl",
+    "hansel-fs": "hansel-few-shot-v1.jsonl",
+    "hansel-zs": "hansel-zero-shot-v1.jsonl",
+}
+
+logger = datasets.logging.get_logger(__name__)
+
+
+class HanselConfig(datasets.BuilderConfig):
+    """BuilderConfig for HanselConfig."""
+
+    def __init__(self, features, data_url, citation, url, **kwargs):
+        """BuilderConfig for Hansel.
+
+        Args:
+          features: `list[string]`, list of the features that will appear in the
+            feature dict. Should not include "label".
+          data_url: `string`, url to download the zip file from.
+          citation: `string`, citation for the data set.
+          url: `string`, url for information about the data set.
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(HanselConfig, self).__init__(version=datasets.Version("1.0.0"), **kwargs)
+        self.features = features
+        self.data_url = data_url
+        self.citation = citation
+        self.url = url
+
+
+class Hansel(datasets.GeneratorBasedBuilder):
+    """The Hansel benchmark."""
+
+    BUILDER_CONFIGS = [
+        HanselConfig(
+            name="wiki",
+            description=_HANSEL_DESCRIPTION,
+            features=["id", "text", "start", "end", "mention", "gold_id"],
+            data_url="https://huggingface.co/datasets/HIT-TMG/Hansel/blob/main/",
+            citation=_HANSEL_CITATION,
+            url="https://github.com/HITsz-TMG/Hansel",
+        )
+        HanselConfig(
+            name="hansel-few-shot",
+            description=_HANSEL_DESCRIPTION,
+            features=["id", "text", "start", "end", "mention", "gold_id", "source", "domain"],
+            data_url="https://huggingface.co/datasets/HIT-TMG/Hansel/blob/main/",
+            citation=_HANSEL_CITATION,
+            url="https://github.com/HITsz-TMG/Hansel",
+        )
+        HanselConfig(
+            name="hansel-zero-shot",
+            description=_HANSEL_DESCRIPTION,
+            features=["id", "text", "start", "end", "mention", "gold_id", "source", "domain"],
+            data_url="https://huggingface.co/datasets/HIT-TMG/Hansel/blob/main/",
+            citation=_HANSEL_CITATION,
+            url="https://github.com/HITsz-TMG/Hansel",
+        )
+    ]
+
+    def _info(self):
+        features = {feature: datasets.Value("string") for feature in self.config.features}
+        features["start"] = datasets.Value("int64")
+        features["end"] = datasets.Value("int64")
+
+        return datasets.DatasetInfo(
+            description=self.config.description,
+            features=datasets.Features(features),
+            homepage=self.config.url,
+            citation=self.config.citation
+        )
+
+
+    def _split_generators(self, dl_manager):
+
+        urls_to_download = self._URLS
+        downloaded_files = dl_manager.download_and_extract(urls_to_download)
+
+        if "hansel-few" in self.config.name:
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TEST,
+                    gen_kwargs={
+                        "data_file": downloaded_files["hansel-fs"]),
+                        "split": datasets.Split.TEST,
+                    },
+                ),
+            ]
+        if "hansel-zero" in self.config.name:
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TEST,
+                    gen_kwargs={
+                        "data_file": downloaded_files["hansel-zs"],
+                        "split": datasets.Split.TEST,
+                    },
+                ),
+            ]
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "data_file": downloaded_files["train"],
+                    "split": datasets.Split.TRAIN,
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "data_file": downloaded_files["val"],
+                    "split": datasets.Split.VALIDATION,
+                },
+            ),
+        ]
+
+    def _generate_examples(self, data_file, split):
+        logger.info("generating examples from = %s", data_file)
+        with open(data_file, encoding="utf-8") as f:
+            for line in f:
+                temDict = json.loads(line)
+                key = temDict["id"]
+                if "hansel" in self.config.name:
+                    yield key, {
+                                "text": temDict["text"],
+                                "start": temDict["start"],
+                                "end": temDict["end"],
+                                "mention": temDict["mention"],
+                                "gold_id": temDict["gold_id"],
+                                "source": temDict["source"],
+                                "domain": temDict["domain"],
+                            }
+                else:
+                    yield key, {
+                                "text": temDict["text"],
+                                "start": temDict["start"],
+                                "end": temDict["end"],
+                                "mention": temDict["mention"],
+                                "gold_id": temDict["gold_id"],
+                            }