A crowdsourced dataset of dialogues grounded in social contexts involving utilization of commonsense.

Overview

Commonsense-Dialogues Dataset

We present Commonsense-Dialogues, a crowdsourced dataset of ~11K dialogues grounded in social contexts involving utilization of commonsense. The social contexts used were sourced from the train split of the SocialIQA dataset, a multiple-choice question-answering based social commonsense reasoning benchmark.

For the collection of the Commonsense-Dialogues dataset, each Turker was presented a social context and asked to write a dialogue of 4-6 turns between two people based on the event(s) described in the context. The Turker was asked to alternate between the roles of an individual referenced in the context and a 3rd party friend. See the following dialogues as examples:

    "1": {  # dialogue_id
        "context": "Sydney met Carson's mother for the first time last week. He liked her.",   # multiple individuals in the context: Sydney and Carson
        "speaker": "Sydney",   # role 1 = Sydney, role 2 = a third-person friend of Sydney
        "turns": [
            "I met Carson's mother last week for the first time.",
            "How was she?",
            "She turned out to be really nice. I like her.",
            "That's good to hear.",
            "It is, especially since Carson and I are getting serious.",
            "Well, at least you'll like your in-law if you guys get married."
        ]
    }

    "2": {
        "context": "Kendall had a party at Jordan's house but was found out to not have asked and just broke in.",
        "speaker": "Kendall",
        "turns": [
            "Did you hear about my party this weekend at Jordan\u2019s house?",
            "I heard it was amazing, but that you broke in.",
            "That was a misunderstanding, I had permission to be there.",
            "Who gave you permission?",
            "I talked to Jordan about it months ago before he left town to go to school, but he forgot to tell his roommates about it.",
            "Ok cool, I hope everything gets resolved."
        ]
    }

The data can be found in the /data directory of this repo. train.json has ~9K dialogues, valid.json and test.json have ~1K dialogues each. Since all the contexts were sourced from the train split of SocialIQA, it is imperative to note that any form of multi-task training and evaluation with Commonsense-Dialogues and SocialIQA must be done with caution to ensure fair and accurate conclusions.

Some statistics about the data are provided below:

Stat Train Valid Test
# of dialogues 9058 1157 1158
average # of turns in a dialogue 5.72 5.72 5.71
average # of words in a turn 12.4 12.4 12.2
# of distinct SocialIQA contexts used 3672 483 473
average # of dialogues for a SocialIQA context 2.46 2.395 2.45

Security

See CONTRIBUTING for more information.

License

This repository is licensed under the CC-BY-NC 4.0 License.

Citation

If you use this dataset, please cite the following paper:

@inproceedings{zhou-etal-2021-commonsense,
    title = "Commonsense-Focused Dialogues for Response Generation: An Empirical Study",
    author = "Zhou, Pei  and
      Gopalakrishnan, Karthik  and
      Hedayatnia, Behnam  and
      Kim, Seokhwan  and
      Pujara, Jay  and
      Ren, Xiang  and
      Liu, Yang  and
      Hakkani-Tur, Dilek",
    booktitle = "Proceedings of the 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue",
    year = "2021",
    address = "Singapore and Online",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/2109.06427"
}

Note that the paper uses newly collected dialogues as well as those that were filtered from existing datasets. This repo contains our newly collected dialogues alone.

Owner
Alexa
Alexa
[AAAI 21] Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised Learning

◥ Curriculum Labeling ◣ Revisiting Pseudo-Labeling for Semi-Supervised Learning Paola Cascante-Bonilla, Fuwen Tan, Yanjun Qi, Vicente Ordonez. In the

UVA Computer Vision 113 Dec 15, 2022
Just a Basic like Language for Zeno INC

zeno-basic-language Just a Basic like Language for Zeno INC This is written in 100% python. this is basic language like language. so its not for big p

Voidy Devleoper 1 Dec 18, 2021
Guide: Finetune GPT2-XL (1.5 Billion Parameters) and GPT-NEO (2.7 B) on a single 16 GB VRAM V100 Google Cloud instance with Huggingface Transformers using DeepSpeed

Guide: Finetune GPT2-XL (1.5 Billion Parameters) and GPT-NEO (2.7 Billion Parameters) on a single 16 GB VRAM V100 Google Cloud instance with Huggingfa

289 Jan 06, 2023
BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model

BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model

303 Dec 17, 2022
A framework for cleaning Chinese dialog data

A framework for cleaning Chinese dialog data

Yida 136 Dec 20, 2022
Universal End2End Training Platform, including pre-training, classification tasks, machine translation, and etc.

背景 安装教程 快速上手 (一)预训练模型 (二)机器翻译 (三)文本分类 TenTrans 进阶 1. 多语言机器翻译 2. 跨语言预训练 背景 TrenTrans是一个统一的端到端的多语言多任务预训练平台,支持多种预训练方式,以及序列生成和自然语言理解任务。 安装教程 git clone git

Tencent Minority-Mandarin Translation Team 42 Dec 20, 2022
Easy-to-use CPM for Chinese text generation

CPM 项目描述 CPM(Chinese Pretrained Models)模型是北京智源人工智能研究院和清华大学发布的中文大规模预训练模型。官方发布了三种规模的模型,参数量分别为109M、334M、2.6B,用户需申请与通过审核,方可下载。 由于原项目需要考虑大模型的训练和使用,需要安装较为复杂

382 Jan 07, 2023
An assignment from my grad-level data mining course demonstrating some experience with NLP/neural networks/Pytorch

NLP-Pytorch-Assignment An assignment from my grad-level data mining course (before I started personal projects) demonstrating some experience with NLP

David Thorne 0 Feb 06, 2022
無料で使える中品質なテキスト読み上げソフトウェア、VOICEVOXの音声合成エンジン

VOICEVOX ENGINE VOICEVOXの音声合成エンジン。 実態は HTTP サーバーなので、リクエストを送信すればテキスト音声合成できます。 API ドキュメント VOICEVOX ソフトウェアを起動した状態で、ブラウザから

Hiroshiba 3 Jul 05, 2022
Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition, Part-of-Speech Tagging and so on.

anaGo anaGo is a Python library for sequence labeling(NER, PoS Tagging,...), implemented in Keras. anaGo can solve sequence labeling tasks such as nam

Hiroki Nakayama 1.5k Dec 05, 2022
Code for the paper "Are Sixteen Heads Really Better than One?"

Are Sixteen Heads Really Better than One? This repository contains code to reproduce the experiments in our paper Are Sixteen Heads Really Better than

Paul Michel 143 Dec 14, 2022
In this project, we aim to achieve the task of predicting emojis from tweets. We aim to investigate the relationship between words and emojis.

Making Emojis More Predictable by Karan Abrol, Karanjot Singh and Pritish Wadhwa, Natural Language Processing (CSE546) under the guidance of Dr. Shad

Karanjot Singh 2 Jan 17, 2022
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding

⚠️ Checkout develop branch to see what is coming in pyannote.audio 2.0: a much smaller and cleaner codebase Python-first API (the good old pyannote-au

pyannote 2.2k Jan 09, 2023
**NSFW** A chatbot based on GPT2-chitchat

DangBot -- 好怪哦,再来一句 卡群怪话bot,powered by GPT2 for Chinese chitchat Training Example: python train.py --lr 5e-2 --epochs 30 --max_len 300 --batch_size 8

Tommy Yang 11 Jul 21, 2022
Chinese Grammatical Error Diagnosis

nlp-CGED Chinese Grammatical Error Diagnosis 中文语法纠错研究 基于序列标注的方法 所需环境 Python==3.6 tensorflow==1.14.0 keras==2.3.1 bert4keras==0.10.6 笔者使用了开源的bert4keras

12 Nov 25, 2022
Line as a Visual Sentence: Context-aware Line Descriptor for Visual Localization

Line as a Visual Sentence with LineTR This repository contains the inference code, pretrained model, and demo scripts of the following paper. It suppo

SungHo Yoon 158 Dec 27, 2022
Graph Coloring - Weighted Vertex Coloring Problem

Graph Coloring - Weighted Vertex Coloring Problem This project proposes several local searches and an MCTS algorithm for the weighted vertex coloring

Cyril 1 Jul 08, 2022
Open solution to the Toxic Comment Classification Challenge

Starter code: Kaggle Toxic Comment Classification Challenge More competitions 🎇 Check collection of public projects 🎁 , where you can find multiple

minerva.ml 153 Jun 22, 2022
Searching keywords in PDF file folders

keyword_searching Steps to use this Python scripts: (1)Paste this script into the file folder containing the PDF files you need to search from; (2)Thi

1 Nov 08, 2021