CsFEVER initial descriptors

README.md

@@ -1,3 +1,14 @@
 ---
 license: cc-by-sa-3.0
 ---
+# CsFEVER experimental Fact-Checking dataset
+
+Czech dataset for fact verification localized from the data points of [FEVER](https://arxiv.org/abs/1803.05355) using the localization scheme described in the [CTKFacts: Czech Datasets for Fact Verification](https://arxiv.org/abs/2201.11115) paper which is currently being revised for publication in LREV journal.
+
+The version you are looking at was reformatted to *Claim*-*Evidence* string pairs for the specific task of NLI - a more general Document-Retrieval-ready interpretation of our datapoints which can be used for training and evaluating the DR models over the June 2016 wikipedia snapshot can be found in the [data_dr]() folder in the JSON Lines format.
+
+## Data Statement
+
+### Curation Rationale
+
+TODO

csfever.py

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+import os
+import pathlib
+from typing import overload
+import datasets
+import json
+
+from datasets.info import DatasetInfo
+
+_VERSION = "0.0.1"
+
+_URL= "data/"
+
+_URLS = {
+    "train": _URL + "train.jsonl",
+    "validation": _URL + "validation.jsonl",
+    "test": _URL + "test.jsonl"
+}
+
+_DESCRIPTION = """\
+CsFEVER is a Czech localisation of the English FEVER datgaset.
+"""
+
+_CITATION = """\
+@article{DBLP:journals/corr/abs-2201-11115,
+  author    = {Jan Drchal and
+               Herbert Ullrich and
+               Martin R{\'{y}}par and
+               Hana Vincourov{\'{a}} and
+               V{\'{a}}clav Moravec},
+  title     = {CsFEVER and CTKFacts: Czech Datasets for Fact Verification},
+  journal   = {CoRR},
+  volume    = {abs/2201.11115},
+  year      = {2022},
+  url       = {https://arxiv.org/abs/2201.11115},
+  eprinttype = {arXiv},
+  eprint    = {2201.11115},
+  timestamp = {Tue, 01 Feb 2022 14:59:01 +0100},
+  biburl    = {https://dblp.org/rec/journals/corr/abs-2201-11115.bib},
+  bibsource = {dblp computer science bibliography, https://dblp.org}
+}
+"""
+
+datasets.utils.version.Version
+class CsFever(datasets.GeneratorBasedBuilder):
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("int32"),
+                    "label": datasets.ClassLabel(names=["REFUTES", "NOT ENOUGH INFO", "SUPPORTS"]),
+                    # datasets.features.Sequence({"text": datasets.Value("string"),"answer_start": datasets.Value("int32"),})
+                    "evidence": datasets.Value("string"),
+                    "claim": datasets.Value("string"),
+                }
+            ),
+            # No default supervised_keys (as we have to pass both question
+            # and context as input).
+            supervised_keys=None,
+            version=_VERSION,
+            homepage="https://fcheck.fel.cvut.cz/dataset/",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager):
+        downloaded_files = dl_manager.download_and_extract(_URLS)
+
+        return [
+            datasets.SplitGenerator(datasets.Split.TRAIN, {
+                "filepath": downloaded_files["train"]
+            }),
+            datasets.SplitGenerator(datasets.Split.VALIDATION, {
+                "filepath": downloaded_files["validation"]
+            }),
+            datasets.SplitGenerator(datasets.Split.TEST, {
+                "filepath": downloaded_files["test"]
+            }),
+        ]
+
+    def _generate_examples(self, filepath):
+        """This function returns the examples in the raw (text) form."""
+        key = 0
+        with open(filepath, encoding="utf-8") as f:
+            for line in f:
+                datapoint = json.loads(line)
+                yield key, {
+                    "id": datapoint["id"],
+                    "evidence": " ".join(datapoint["evidence"]),
+                    "claim": datapoint["claim"],
+                    "label": datapoint["label"]
+                }
+                key += 1

experiments.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 🤗 Experiments over hf dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import datasets\n",
+    "from datasets import load_dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Using custom data configuration default\n",
+      "Reusing dataset ctkfacts_nli (/Users/bertik/.cache/huggingface/datasets/ctkfacts_nli/default/0.0.0/5dcd805dfbd9694ead18f5cf4da8d902a1a1ca53685a5ebabd33f3d314dd597d)\n",
+      "100%|██████████| 3/3 [00:00<00:00, 409.28it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "d=load_dataset(\"csfever.py\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "DatasetDict({\n",
+       "    train: Dataset({\n",
+       "        features: ['id', 'label', 'evidence', 'claim'],\n",
+       "        num_rows: 2903\n",
+       "    })\n",
+       "    validation: Dataset({\n",
+       "        features: ['id', 'label', 'evidence', 'claim'],\n",
+       "        num_rows: 377\n",
+       "    })\n",
+       "    test: Dataset({\n",
+       "        features: ['id', 'label', 'evidence', 'claim'],\n",
+       "        num_rows: 431\n",
+       "    })\n",
+       "})"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "d"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "        _|    _|  _|    _|    _|_|_|    _|_|_|  _|_|_|  _|      _|    _|_|_|      _|_|_|_|    _|_|      _|_|_|  _|_|_|_|\n",
+      "        _|    _|  _|    _|  _|        _|          _|    _|_|    _|  _|            _|        _|    _|  _|        _|\n",
+      "        _|_|_|_|  _|    _|  _|  _|_|  _|  _|_|    _|    _|  _|  _|  _|  _|_|      _|_|_|    _|_|_|_|  _|        _|_|_|\n",
+      "        _|    _|  _|    _|  _|    _|  _|    _|    _|    _|    _|_|  _|    _|      _|        _|    _|  _|        _|\n",
+      "        _|    _|    _|_|      _|_|_|    _|_|_|  _|_|_|  _|      _|    _|_|_|      _|        _|    _|    _|_|_|  _|_|_|_|\n",
+      "\n",
+      "        \n",
+      "Username: ^C\n",
+      "Traceback (most recent call last):\n",
+      "  File \"/opt/homebrew/bin/huggingface-cli\", line 8, in <module>\n",
+      "    sys.exit(main())\n",
+      "  File \"/opt/homebrew/lib/python3.9/site-packages/huggingface_hub/commands/huggingface_cli.py\", line 41, in main\n",
+      "    service.run()\n",
+      "  File \"/opt/homebrew/lib/python3.9/site-packages/huggingface_hub/commands/user.py\", line 169, in run\n",
+      "    username = input(\"Username: \")\n",
+      "KeyboardInterrupt\n"
+     ]
+    }
+   ],
+   "source": [
+    "!huggingface-cli login"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading: 100%|██████████| 2.55k/2.55k [00:00<00:00, 1.33MB/s]\n",
+      "Using custom data configuration default\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading and preparing dataset ctkfacts_nli/default to /Users/bertik/.cache/huggingface/datasets/heruberuto___ctkfacts_nli/default/0.0.0/5dcd805dfbd9694ead18f5cf4da8d902a1a1ca53685a5ebabd33f3d314dd597d...\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading: 100%|██████████| 2.14M/2.14M [00:00<00:00, 2.86MB/s]\n",
+      "Downloading: 100%|██████████| 247k/247k [00:00<00:00, 386kB/s]\n",
+      "Downloading: 100%|██████████| 287k/287k [00:00<00:00, 450kB/s]\n",
+      "100%|██████████| 3/3 [00:04<00:00,  1.66s/it]\n",
+      "100%|██████████| 3/3 [00:00<00:00, 976.56it/s]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Dataset ctkfacts_nli downloaded and prepared to /Users/bertik/.cache/huggingface/datasets/heruberuto___ctkfacts_nli/default/0.0.0/5dcd805dfbd9694ead18f5cf4da8d902a1a1ca53685a5ebabd33f3d314dd597d. Subsequent calls will reuse this data.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 3/3 [00:00<00:00, 811.96it/s]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "DatasetDict({\n",
+       "    train: Dataset({\n",
+       "        features: ['id', 'label', 'evidence', 'claim'],\n",
+       "        num_rows: 2903\n",
+       "    })\n",
+       "    validation: Dataset({\n",
+       "        features: ['id', 'label', 'evidence', 'claim'],\n",
+       "        num_rows: 377\n",
+       "    })\n",
+       "    test: Dataset({\n",
+       "        features: ['id', 'label', 'evidence', 'claim'],\n",
+       "        num_rows: 431\n",
+       "    })\n",
+       "})"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "load_dataset(\"heruberuto/ctkfacts_nli\", use_auth_token=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "interpreter": {
+   "hash": "b0fa6594d8f4cbf19f97940f81e996739fb7646882a419484c72d19e05852a7e"
+  },
+  "kernelspec": {
+   "display_name": "Python 3.9.7 64-bit",
+   "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": "3.9.7"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

test.py

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+import datasets
+
+datasets.load_dataset("csfever.py")