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README.md

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----
-annotations_creators:
-- crowdsourced
-language:
-- en
-license:
-- cc-by-nc-sa-4.0
-multilinguality:
-- monolingual
-size_categories:
-- 10K<n<100k
-task_categories:
-- text-retrieval
-- text-generation
-- sequence-modeling
-task_ids:
-- open-domain-cqa
-- conversational-question-answering
-pretty_name: Open-domain Conversational Question Answering with Topic Switching
----
-# Dataset Card for TopiOCQA
-
-## Table of Contents
-- [Dataset Description](#dataset-description)
-  - [Dataset Summary](#dataset-summary)
-  - [Languages](#languages)
-- [Additional Information](#additional-information)
-  - [Licensing Information](#licensing-information)
-  - [Citation Information](#citation-information)
-
-## Dataset Description
-
-- **Homepage:** [TopiOCQA homepage](https://mcgill-nlp.github.io/topiocqa/)
-- **Repository:** [TopiOCQA Github](https://github.com/McGill-NLP/topiocqa)
-- **Paper:** [Open-domain Conversational Question Answering with Topic Switching](https://arxiv.org/abs/2110.00768)
-- **Point of Contact:** [Vaibhav Adlakha](mailto:vaibhav.adlakha@mila.quebec)
-
-### Dataset Summary
-
-TopiOCQA is an information-seeking conversational dataset with challenging topic switching phenomena.
-
-### Languages
-
-The language in the dataset is English as spoken by the crowdworkers. The BCP-47 code for English is en.
-
-## Additional Information
-
-### Licensing Information
-
-TopiOCQA is licensed under a [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License](https://creativecommons.org/licenses/by-nc-sa/4.0/).
-
-### Citation Information
-
-```
-@inproceedings{adlakha2022topiocqa,
-  title={Topi{OCQA}: Open-domain Conversational Question Answering with Topic Switching},
-  author={Adlakha, Vaibhav and Dhuliawala, Shehzaad and Suleman, Kaheer and de Vries, Harm and Reddy, Siva},
-  journal={Transactions of the Association for Computational Linguistics},
-  volume = {10},
-  pages = {468-483},
-  year = {2022},
-  month = {04},
-  year={2022},
-  issn = {2307-387X},
-  doi = {10.1162/tacl_a_00471},
-  url = {https://doi.org/10.1162/tacl\_a\_00471},
-  eprint = {https://direct.mit.edu/tacl/article-pdf/doi/10.1162/tacl\_a\_00471/2008126/tacl\_a\_00471.pdf},
-}
-```

TopiOCQA.py

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-# 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
-"""TopiOCQA: Open-domain Conversational Question Answering with Topic Switching"""
-
-
-import json
-
-import datasets
-# from datasets.tasks import QuestionAnsweringExtractive
-
-
-logger = datasets.logging.get_logger(__name__)
-
-
-_DESCRIPTION = """\
-TopiOCQA is an information-seeking conversational dataset with challenging topic switching phenomena.
-"""
-
-_URLS = {
-    "train": "data/topiocqa_train.jsonl",
-    "valid": "data/topiocqa_valid.jsonl",
-}
-
-
-class TopiOCQAConfig(datasets.BuilderConfig):
-    """BuilderConfig for TopiOCQA."""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig for TopiOCQA.
-
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(TopiOCQAConfig, self).__init__(**kwargs)
-
-
-class TopiOCQA(datasets.GeneratorBasedBuilder):
-    """TopiOCQA: Open-domain Conversational Question Answering with Topic Switching"""
-
-    BUILDER_CONFIGS = [
-        TopiOCQAConfig(
-            name="plain_text",
-            version=datasets.Version("1.0.0", ""),
-            description="Plain text",
-        ),
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "Conversation_no": datasets.Value("int32"),
-                    "Turn_no": datasets.Value("int32"),
-                    "Question": datasets.Value("string"),
-                    "Answer": datasets.Value("string"),
-                    "Topic": datasets.Value("string"),
-                    "Topic_section": datasets.Value("string"),
-                    "Rationale": datasets.Value("string"),
-                    "is_nq": datasets.Value("bool"),
-                    "Context": datasets.features.Sequence(datasets.Value("string")),
-                    "Additional_answers": datasets.features.Sequence(
-                        {
-                            "Answer": datasets.Value("string"),
-                            "Topic": datasets.Value("string"),
-                            "Topic_section": datasets.Value("string"),
-                            "Rationale": datasets.Value("string"),
-                        }
-                    ),
-                }
-            ),
-            supervised_keys=None,
-            homepage="https://mcgill-nlp.github.io/topiocqa/",
-        )
-
-    def _split_generators(self, dl_manager):
-        downloaded_files = dl_manager.download_and_extract(_URLS)
-
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["valid"]}),
-        ]
-
-    def _generate_examples(self, filepath):
-        """This function returns the examples in the raw (text) form."""
-        logger.info("generating examples from = %s", filepath)
-        key = 0
-        with open(filepath, encoding="utf-8") as f:
-            for line in f:
-                data = json.loads(line)
-                yield key, {
-                    "Conversation_no": data["Conversation_no"],
-                    "Turn_no": data["Turn_no"],
-                    "Question": data["Question"],
-                    "Answer": data["Answer"],
-                    "Topic": data["Topic"],
-                    "Topic_section": data["Topic_section"],
-                    "Rationale": data["Rationale"],
-                    "is_nq": data["is_nq"],
-                    "Context": data["Context"],
-                    "Additional_answers": data["Additional_answers"],
-                }
-                key += 1
-

data/topiocqa_train.jsonl → plain_text/topi_ocqa-train.parquet

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