Delete loading script

web_questions.py

@@ -1,98 +0,0 @@
-# coding=utf-8
-# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-# Lint as: python3
-"""WebQuestions Benchmark for Question Answering."""
-
-
-import json
-import re
-
-import datasets
-
-
-_CITATION = """
-@inproceedings{berant-etal-2013-semantic,
-    title = "Semantic Parsing on {F}reebase from Question-Answer Pairs",
-    author = "Berant, Jonathan  and
-      Chou, Andrew  and
-      Frostig, Roy  and
-      Liang, Percy",
-    booktitle = "Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing",
-    month = oct,
-    year = "2013",
-    address = "Seattle, Washington, USA",
-    publisher = "Association for Computational Linguistics",
-    url = "https://www.aclweb.org/anthology/D13-1160",
-    pages = "1533--1544",
-}
-"""
-_SPLIT_DOWNLOAD_URL = {
-    "train": "https://worksheets.codalab.org/rest/bundles/0x4a763f8cde224c2da592b75f29e2f5c2/contents/blob/",
-    "test": "https://worksheets.codalab.org/rest/bundles/0xe7bac352fce7448c9ef238fb0a297ec2/contents/blob/",
-}
-
-_DESCRIPTION = """\
-This dataset consists of 6,642 question/answer pairs.
-The questions are supposed to be answerable by Freebase, a large knowledge graph.
-The questions are mostly centered around a single named entity.
-The questions are popular ones asked on the web (at least in 2013).
-"""
-
-
-class WebQuestions(datasets.GeneratorBasedBuilder):
-    """WebQuestions Benchmark for Question Answering."""
-
-    VERSION = datasets.Version("1.0.0")
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "url": datasets.Value("string"),
-                    "question": datasets.Value("string"),
-                    "answers": datasets.features.Sequence(datasets.Value("string")),
-                }
-            ),
-            supervised_keys=None,
-            homepage="https://worksheets.codalab.org/worksheets/0xba659fe363cb46e7a505c5b6a774dc8a",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        file_paths = dl_manager.download(_SPLIT_DOWNLOAD_URL)
-
-        return [
-            datasets.SplitGenerator(name=split, gen_kwargs={"file_path": file_path})
-            for split, file_path in file_paths.items()
-        ]
-
-    def _generate_examples(self, file_path):
-        """Parses split file and yields examples."""
-
-        def _target_to_answers(target):
-            target = re.sub(r"^\(list |\)$", "", target)
-            return ["".join(ans) for ans in re.findall(r'\(description (?:"([^"]+?)"|([^)]+?))\)\w*', target)]
-
-        with open(file_path, encoding="utf-8") as f:
-            examples = json.load(f)
-            for i, ex in enumerate(examples):
-                yield i, {
-                    "url": ex["url"],
-                    "question": ex["utterance"],
-                    "answers": _target_to_answers(ex["targetValue"]),
-                }