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README.md

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----
-annotations_creators:
-- no-annotation
-language_creators:
-- found
-language:
-- zh
-license:
-- other
-multilinguality:
-- monolingual
-paperswithcode_id: personaldialog
-pretty_name: "PersonalDialog"
-size_categories:
-- 10M<n<100M
-source_datasets:
-- original
-task_categories:
-- conversational
-task_ids:
-- dialogue-generation
----
-
-# Dataset Card for PersonalDialog
-
-## Table of Contents
-- [Dataset Card for PersonalDialog](#dataset-card-for-personaldialog)
-  - [Table of Contents](#table-of-contents)
-  - [Dataset Description](#dataset-description)
-    - [Dataset Summary](#dataset-summary)
-    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
-    - [Languages](#languages)
-  - [Dataset Structure](#dataset-structure)
-    - [Data Instances](#data-instances)
-    - [Data Fields](#data-fields)
-    - [Data Splits](#data-splits)
-  - [Dataset Creation](#dataset-creation)
-    - [Curation Rationale](#curation-rationale)
-    - [Source Data](#source-data)
-      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
-      - [Who are the source language producers?](#who-are-the-source-language-producers)
-    - [Annotations](#annotations)
-      - [Annotation process](#annotation-process)
-      - [Who are the annotators?](#who-are-the-annotators)
-    - [Personal and Sensitive Information](#personal-and-sensitive-information)
-  - [Considerations for Using the Data](#considerations-for-using-the-data)
-    - [Social Impact of Dataset](#social-impact-of-dataset)
-    - [Discussion of Biases](#discussion-of-biases)
-    - [Other Known Limitations](#other-known-limitations)
-  - [Additional Information](#additional-information)
-    - [Dataset Curators](#dataset-curators)
-    - [Licensing Information](#licensing-information)
-    - [Citation Information](#citation-information)
-    - [Contributions](#contributions)
-
-## Dataset Description
-
-- **Homepage:** https://www.zhengyinhe.com/datasets/
-- **Repository:** https://github.com/silverriver/PersonalDilaog
-- **Paper:** https://arxiv.org/abs/1901.09672
-
-### Dataset Summary
-
-The PersonalDialog dataset is a large-scale multi-turn Chinese dialogue dataset containing various traits from a large number of speakers.
-We are releasing about 5M sessions of carefully filtered dialogues.
-Each utterance in PersonalDialog is associated with a speaker marked with traits like Gender, Location, Interest Tags.
-
-### Supported Tasks and Leaderboards
-
-- dialogue-generation: The dataset can be used to train a model for generating dialogue responses.
-- response-retrieval: The dataset can be used to train a reranker model that can be used to implement a retrieval-based dialogue model.
-
-### Languages
-
-PersonalDialog is in Chinese
-
-PersonalDialog中的对话是中文的
-
-## Dataset Structure
-
-### Data Instances
-
-`train` split:
-
-```json
-{
-  "dialog": ["那么 晚", "加班 了 刚 到 家 呀 ！", "吃饭 了 么", "吃 过 了 ！"], 
-  "profile": [
-    { 
-      "tag": ["间歇性神经病", "爱笑的疯子", "他们说我犀利", "爱做梦", "自由", "旅游", "学生", "双子座", "好性格"], 
-      "loc": "福建 厦门", "gender": "male"
-    }, {
-      "tag": ["设计师", "健康养生", "热爱生活", "善良", "宅", "音樂", "时尚"], 
-      "loc": "山东 济南", "gender": "male"
-      }
-  ], 
-  "uid": [0, 1, 0, 1],
-}
-```
-
-`dev` and `test` split:
-
-```json
-{
-  "dialog": ["没 人性 啊 ！", "可以 来 组织 啊", "来 上海 陪姐 打 ？"], 
-  "profile": [
-    {"tag": [""], "loc": "上海 浦东新区", "gender": "female"}, 
-    {"tag": ["嘉庚", "keele", "leicester", "UK", "泉州五中"], "loc": "福建 泉州", "gender": "male"},
-  ], 
-  "uid": [0, 1, 0],
-  "responder_profile": {"tag": ["嘉庚", "keele", "leicester", "UK", "泉州五中"], "loc": "福建 泉州", "gender": "male"}, 
-  "golden_response": "吴经理 派车来 小 泉州 接 么 ？", 
-  "is_biased": true,
-}
-```
-
-### Data Fields
-
-- `dialog` (list of strings): List of utterances consisting of a dialogue.
-- `profile` (list of dicts): List of profiles associated with each speaker.
-- `tag` (list of strings): List of tags associated with each speaker.
-- `loc` (string): Location of each speaker.
-- `gender` (string): Gender of each speaker.
-- `uid` (list of int): Speaker id for each utterance in the dialogue.
-- `responder_profile` (dict): Profile of the responder. (Only available in `dev` and `test` split)
-- `golden_response` (str): Response of the responder. (Only available in `dev` and `test` split)
-- `id_biased` (bool): Whether the dialogue is guranteed to be persona related or not. (Only available in `dev` and `test` split)
-
-### Data Splits
-
-
-|train|valid|test|
-|---:|---:|---:|
-|5,438,165 | 10,521 | 10,523 |
-
-
-## Dataset Creation
-
-### Curation Rationale
-
-[Needs More Information]
-
-### Source Data
-
-#### Initial Data Collection and Normalization
-
-[Needs More Information]
-
-#### Who are the source language producers?
-
-[Needs More Information]
-
-### Annotations
-
-#### Annotation process
-
-[Needs More Information]
-
-#### Who are the annotators?
-
-[Needs More Information]
-
-### Personal and Sensitive Information
-
-[Needs More Information]
-
-## Considerations for Using the Data
-
-### Social Impact of Dataset
-
-[Needs More Information]
-
-### Discussion of Biases
-
-[Needs More Information]
-
-### Other Known Limitations
-
-[Needs More Information]
-
-## Additional Information
-
-### Dataset Curators
-
-[Needs More Information]
-
-### Licensing Information
-
-other-weibo
-
-This dataset is collected from Weibo.
-You can refer to the [detailed policy](https://weibo.com/signup/v5/privacy) required to use this dataset.
-Please restrict the usage of this dataset to non-commerical purposes.
-
-### Citation Information
-
-```bibtex
-@article{zheng2019personalized,
-  title   = {Personalized dialogue generation with diversified traits},
-  author  = {Zheng, Yinhe and Chen, Guanyi and Huang, Minlie and Liu, Song and Zhu, Xuan},
-  journal = {arXiv preprint arXiv:1901.09672},
-  year    = {2019}
-}
-
-@inproceedings{zheng2020pre,
-  title     = {A pre-training based personalized dialogue generation model with persona-sparse data},
-  author    = {Zheng, Yinhe and Zhang, Rongsheng and Huang, Minlie and Mao, Xiaoxi},
-  booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
-  volume    = {34},
-  number    = {05},
-  pages     = {9693--9700},
-  year      = {2020}
-}
-```
-
-### Contributions
-
-Thanks to [Yinhe Zheng](https://github.com/silverriver) for adding this dataset.

dataset_infos.json

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personal_dialog.py

@@ -1,175 +0,0 @@
-# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
-#
-# 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.
-"""
-The PersonalDialog dataset is a large-scale multi-turn Chinese dialogue dataset containing various traits from a large number of speakers.
-We are releasing about 5M sessions of carefully filtered dialogues.
-Each utterance in PersonalDialog is associated with a speaker marked with traits like Gender, Location, Interest Tags.
-"""
-
-import json
-
-import datasets
-
-
-_CITATION = """\
-@article{zheng2019personalized,
-  title   = {Personalized dialogue generation with diversified traits},
-  author  = {Zheng, Yinhe and Chen, Guanyi and Huang, Minlie and Liu, Song and Zhu, Xuan},
-  journal = {arXiv preprint arXiv:1901.09672},
-  year    = {2019}
-}
-
-@inproceedings{zheng2020pre,
-  title     = {A pre-training based personalized dialogue generation model with persona-sparse data},
-  author    = {Zheng, Yinhe and Zhang, Rongsheng and Huang, Minlie and Mao, Xiaoxi},
-  booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
-  volume    = {34},
-  number    = {05},
-  pages     = {9693--9700},
-  year      = {2020}
-}
-"""
-
-_DESCRIPTION = """\
-The PersonalDialog dataset is a large-scale multi-turn Chinese dialogue dataset containing various traits from a large number of speakers.
-We are releasing about 5M sessions of carefully filtered dialogues.
-Each utterance in PersonalDialog is associated with a speaker marked with traits like Gender, Location, Interest Tags.
-"""
-
-_HOMEPAGE = "https://github.com/silverriver/PersonalDilaog"
-
-_LICENSE = "MIT"
-
-_URLS = {
-    "valid": [
-        "https://huggingface.co/datasets/silver/personal_dialog/resolve/main/dev_biased.jsonl.gz",
-        "https://huggingface.co/datasets/silver/personal_dialog/resolve/main/dev_random.jsonl.gz",
-    ],
-    "train": "https://huggingface.co/datasets/silver/personal_dialog/resolve/main/dialogues_train.jsonl.gz",
-    "test": [
-        "https://huggingface.co/datasets/silver/personal_dialog/resolve/main/test_biased.jsonl.gz",
-        "https://huggingface.co/datasets/silver/personal_dialog/resolve/main/test_random.jsonl.gz",
-    ],
-}
-
-
-class PersonalDialog(datasets.GeneratorBasedBuilder):
-    """Chinese Dialogues with Personal Traits."""
-
-    VERSION = datasets.Version("1.0.0")
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "dialog": [datasets.Value("string")],
-                "profile": [
-                    {
-                        "tag": [datasets.Value("string")],
-                        "loc": datasets.Value("string"),
-                        "gender": datasets.Value("string"),
-                    }
-                ],
-                "uid": [datasets.Value("int32")],
-                "responder_profile": {
-                    "tag": [datasets.Value("string")],
-                    "loc": datasets.Value("string"),
-                    "gender": datasets.Value("string"),
-                },
-                "golden_response": datasets.Value("string"),
-                "is_biased": datasets.Value("bool"),
-            }
-        )
-        return datasets.DatasetInfo(
-            # This is the description that will appear on the datasets page.
-            description=_DESCRIPTION,
-            # This defines the different columns of the dataset and their types
-            features=features,  # Here we define them above because they are different between the two configurations
-            # If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and
-            # specify them. They'll be used if as_supervised=True in builder.as_dataset.
-            # supervised_keys=("sentence", "label"),
-            # Homepage of the dataset for documentation
-            homepage=_HOMEPAGE,
-            # License for the dataset if available
-            license=_LICENSE,
-            # Citation for the dataset
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        urls = _URLS
-        data_dir = dl_manager.download_and_extract(urls)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "data_files": [data_dir["train"]],
-                    "split": "train",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "data_files": [data_dir["valid"][0], data_dir["valid"][1]],
-                    "split": "valid",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "data_files": [data_dir["test"][0], data_dir["test"][1]],
-                    "split": "test",
-                },
-            ),
-        ]
-
-    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
-    def _generate_examples(self, data_files, split):
-        id = 0
-        for file_i, data_file in enumerate(data_files):
-            with open(data_file, encoding="utf-8") as f:
-                for line in f:
-                    line = line.strip()
-                    if len(line) == 0:
-                        continue
-                    line = json.loads(line)
-
-                    profile = [
-                        {"tag": i["tag"][0].split(";"), "loc": i["loc"], "gender": i["gender"]}
-                        for i in line["profile"]
-                    ]
-                    dialog = [i[0] for i in line["dialog"]]
-
-                    if split == "train":
-                        yield id, {
-                            "dialog": dialog,
-                            "profile": profile,
-                            "uid": line["uid"],
-                            "responder_profile": None,
-                            "golden_response": None,
-                            "is_biased": None,
-                        }
-                    else:
-                        yield id, {
-                            "dialog": dialog,
-                            "profile": profile,
-                            "uid": line["uid"],
-                            "responder_profile": {
-                                "tag": line["responder_profile"]["tag"][0].split(";"),
-                                "loc": line["responder_profile"]["loc"],
-                                "gender": line["responder_profile"]["gender"],
-                            },
-                            "golden_response": line["golden_response"][0],
-                            "is_biased": True if file_i == 0 else False,
-                        }
-                    id += 1

test_random.jsonl.gz

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