Upload JAQKET.py

JAQKET.py

@@ -0,0 +1,128 @@
+import json
+import random
+import string
+import warnings
+from typing import Dict, List, Optional, Union
+
+import datasets as ds
+import pandas as pd
+
+_CITATION = """
+@InProceedings{Kurihara_nlp2020,
+  author =  "鈴木正敏 and 鈴木潤 and 松田耕史 and ⻄田京介 and 井之上直也",
+  title =   "JAQKET: クイズを題材にした日本語 QA データセットの構築",
+  booktitle =   "言語処理学会第26回年次大会",
+  year =    "2020",
+  url = "https://www.anlp.jp/proceedings/annual_meeting/2020/pdf_dir/P2-24.pdf"
+  note= "in Japanese"
+"""
+
+_DESCRIPTION = """\
+JAQKET: JApanese Questions on Knowledge of EnTitie
+"""
+
+_HOMEPAGE = "https://sites.google.com/view/project-aio/dataset"
+
+_LICENSE = """\
+This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
+"""
+
+_DESCRIPTION_CONFIGS = {
+    "v2.0": "v2.0",
+}
+
+_URLS = {
+    "v2.0": {
+        "train": "https://huggingface.co/datasets/kumapo/JAQKET/resolve/main/train_jaqket_59.350.json",
+        "dev": "https://huggingface.co/datasets/kumapo/JAQKET/resolve/main/dev_jaqket_59.350.json",
+    },
+}
+
+def dataset_info_v2() -> ds.Features:
+    features = ds.Features(
+        {
+            "qid": ds.Value("string"),
+            "question": ds.Value("string"),
+            "answers": ds.Sequence({
+                "text": ds.Value("string")
+            }),
+            "ctxs": ds.Sequence({
+                "id": ds.Value("string"),
+                "title": ds.Value("string"),
+                "text": ds.Value("string"),
+                "score": ds.Value("float32"),
+                "has_answer": ds.Value("bool"),
+            })
+        }
+    )
+    return ds.DatasetInfo(
+        description=_DESCRIPTION,
+        citation=_CITATION,
+        homepage=_HOMEPAGE,
+        license=_LICENSE,
+        features=features,
+    )
+
+
+class JAQKET(ds.GeneratorBasedBuilder):
+    VERSION = ds.Version("0.1.0")
+    BUILDER_CONFIGS = [
+        ds.BuilderConfig(
+            name="v2.0",
+            version=VERSION,
+            description=_DESCRIPTION_CONFIGS["v2.0"],
+        ),
+    ]
+
+    def _info(self) -> ds.DatasetInfo:
+        if self.config.name == "v2.0":
+            return dataset_info_v2()
+        else:
+            raise ValueError(f"Invalid config name: {self.config.name}")
+
+    def _split_generators(self, dl_manager: ds.DownloadManager):
+        file_paths = dl_manager.download_and_extract(_URLS[self.config.name])
+        return [
+            ds.SplitGenerator(
+                name=ds.Split.TRAIN,
+                gen_kwargs={"file_path": file_paths["train"]},
+            ),
+            ds.SplitGenerator(
+                name=ds.Split.VALIDATION,
+                gen_kwargs={"file_path": file_paths["valid"]},
+            ),
+        ]
+
+    def _generate_examples(
+        self,
+        file_path: Optional[str] = None,
+        split_df: Optional[pd.DataFrame] = None,
+    ):
+        if file_path is None:
+            raise ValueError(f"Invalid argument for {self.config.name}")
+
+        with open(file_path, "r") as rf:
+            json_data = json.load(rf)
+
+        for json_dict in json_data:
+            q_id = json_dict["qid"]
+            question = json_dict["question"]
+            answers = [{"text": answer} for answer in json_dict["answers"]]
+            ctxs = [
+                {
+                    "id": ctx["id"],
+                    "title": ctx["title"],
+                    "text": ctx["text"],
+                    "score": float(ctx["score"]),
+                    "has_answer": ctx["has_answer"]
+
+                }
+                for ctx in json_dict["ctxs"]
+            ]
+            example_dict = {
+                "qid": q_id,
+                "question": question,
+                "answers": answers,
+                "ctxs": ctxs
+            }
+            yield q_id, example_dict