Add dataset files

README.md

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+# wikidata-rubq-hf
+
+Huggingface Dataset wrapper for Wikidata-RuBQ 2.0 dataset
+
+### Usage
+
+```bash
+git clone [email protected]:s-nlp/wikidata-rubq-hf.git wikidata_rubq
+```
+
+```python3
+from datasets import load_dataset;
+load_dataset('wikidata_rubq.py', 'multiple_en', cache_dir='.', ignore_verifications=True)
+```

example.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "id": "f3362bd9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from transformers import PreTrainedTokenizer\n",
+    "from typing import Dict\n",
+    "import datasets"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "id": "8f447e4f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading and preparing dataset wikidata_rubq/multiple_en to /Users/m.shark/Documents/kq/cache/wikidata_rubq/multiple_en/0.0.1/876b4a13a1f967200cf24bbd09889db3ec1eaff98704d1f0cc7e278c5c1eac85...\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "c4460055d51c4041ac93247920423c49",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading data files:   0%|          | 0/2 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "f2c8e5a312434deeaed87df460b3ef69",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading data:   0%|          | 0.00/619k [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "6c30eb720a544bd6ad3606ef0a1b0ae9",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading data:   0%|          | 0.00/158k [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "64d46fddb2194c90b2474d791ffcd11a",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Extracting data files:   0%|          | 0/2 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Generating validation split: 0 examples [00:00, ? examples/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Generating test split: 0 examples [00:00, ? examples/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Dataset wikidata_rubq downloaded and prepared to /Users/m.shark/Documents/kq/cache/wikidata_rubq/multiple_en/0.0.1/876b4a13a1f967200cf24bbd09889db3ec1eaff98704d1f0cc7e278c5c1eac85. Subsequent calls will reuse this data.\n"
+     ]
+    }
+   ],
+   "source": [
+    "from datasets import load_dataset\n",
+    "dataset = load_dataset(\n",
+    "    'wikidata_rubq.py', 'multiple_en', \n",
+    "    cache_dir='cache', \n",
+    "    ignore_verifications=True, split = 'test')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "id": "849bd722",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "6b30ff22b4794a4da4ae8e3f4949a3a5",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/2 [00:00<?, ?ba/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "dataset = dataset.filter(lambda example: isinstance(example[\"object\"], str))"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

wikidata_rubq.py

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+import datasets
+import os
+import json
+import wikidata
+import pickle
+from wikidata.client import Client
+
+client = Client()
+
+_DESCRIPTION = """\
+HuggingFace wrapper for https://github.com/vladislavneon/RuBQ dataset
+"""
+
+_HOMEPAGE = "https://zenodo.org/record/4345697#.Y01k81JBy3I"
+
+
+_LICENSE = "Attribution-ShareAlike 4.0 International"
+
+_LANGS = ["ru","en"]
+
+
+_URLS = {
+    "test": "https://raw.githubusercontent.com/vladislavneon/RuBQ/master/RuBQ_2.0/RuBQ_2.0_test.json",
+    "dev": "https://raw.githubusercontent.com/vladislavneon/RuBQ/master/RuBQ_2.0/RuBQ_2.0_dev.json",
+}
+
+
+_DATA_DIRECTORY = "."
+VERSION = datasets.Version("0.0.1")
+
+
+class WikidataRuBQConfig(datasets.BuilderConfig):
+    """BuilderConfig for WikidataRuBQ."""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for WikidataRuBQ.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(WikidataRuBQConfig, self).__init__(**kwargs)
+
+
+class WikidataRuBQ(datasets.GeneratorBasedBuilder):
+    """HuggingFace wrapper https://github.com/vladislavneon/RuBQ/tree/master/RuBQ_2.0 dataset"""
+
+    BUILDER_CONFIG_CLASS = WikidataRuBQConfig
+    BUILDER_CONFIGS = []
+    BUILDER_CONFIGS += [
+        WikidataRuBQConfig(
+            name=f"multiple_{ln}",
+            version=VERSION,
+            description="questions with russian multiple labels as answers",
+        )
+        for ln in _LANGS
+    ]
+
+    DEFAULT_CONFIG_NAME = "multiple_en"
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "object": datasets.Sequence(datasets.Value("string")),
+                "question": datasets.Value("string")
+            }
+        )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+        )
+
+    def _split_generators(self, dl_manager):
+        if self.config.name == "default":
+            version, lang = "multiple", "en"
+        else:
+            version, lang = self.config.name.split("_")
+
+        if lang not in _LANGS:
+            raise ValueError(f"Language {lang} not supported")
+
+        downloaded_files = dl_manager.download_and_extract(_URLS)
+
+        data_dir = os.path.join(self.base_path, '')
+        vocab_path = os.path.join(data_dir, "reverse_vocab_wikidata_en.json")
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": downloaded_files["dev"],
+                    "lang": lang,
+                    "vocab_path": vocab_path,
+                    "split": 'train',
+                    "data_dir": data_dir
+                }),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "filepath": downloaded_files["dev"],
+                    "lang": lang,
+                    "vocab_path": vocab_path,
+                    "split": 'validation',
+                    "data_dir": data_dir
+                }),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": downloaded_files["test"],
+                    "lang": lang,
+                    "vocab_path": vocab_path,
+                    "split": 'test',
+                    "data_dir": data_dir
+                })
+        ]
+
+    def get_name(self, idd):
+        '''
+        This function returns a name of an entity and its description given WikiData id
+        input:  (str) wikidata id, e.x. 'Q2'
+        output: (str) concatenated 'name, description' of a given entity
+        '''
+        entity = client.get(idd, load=True)
+        name = None
+        try:
+            name = entity.data["labels"]["en"]["value"]
+        except:
+            pass
+        return name
+
+    def _generate_examples(self, filepath, lang, vocab_path, split, data_dir):
+        direct_path = os.path.join(data_dir, f"{split}_direct_vocab_wikidata_en.pkl")
+
+        with open(direct_path, 'rb') as handle:
+            direct_vocab = pickle.load(handle)
+
+        with open(filepath, encoding="utf-8") as f:
+            item = json.load(f)
+            uid_slide = 0
+            for i in item:
+                question = i['question_text'] if lang == 'ru' else i['question_eng']
+
+                objects = list(set(
+                    [answer['value'].split('entity/')[1] for answer in i['answers'] if '/Q' in answer['value']]
+                ))
+
+                if len(set(objects)) >= 1:
+                    if split == 'train':
+                        for obj in set(objects):
+                            key = i['uid'] + uid_slide
+                            resolved_obj = direct_vocab.get(obj, None)
+                            if resolved_obj is not None:
+                                resolved_obj = resolved_obj[0].upper() + resolved_obj[1:]
+
+                                uid_slide += 1
+
+                                yield (
+                                    key,
+                                    {
+                                        "object": [resolved_obj],
+                                        "question": question,
+                                    }
+                                )
+                    else:
+                        key = i['uid'] + uid_slide
+                        yield (
+                            key,
+                            {
+                                "object": objects,
+                                "question": question,
+                            }
+                        )