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Dataset Card for PEC
Dataset Summary
The PEC dataset is an English-language dataset of open-domain conversations gathered from two subreddits on Reddit, i.e., happy and offmychest. PEC has around 350K persona-based empathetic conversations. Each utterance is associated with a speaker, and each speaker has a persona of multiple persona sentences. The conversations in PEC are more empathetic than casual conversations. The conversations in the happy domain are mostly positive, whereas the conversations in the offmychest domain are mostly negative.
Supported Tasks and Leaderboards
dialogue-modeling
,utterance-retrieval
: this dataset can be used to train a generative or retrieval-based conversational model.
Languages
English
Dataset Structure
Data Instances
A typical data example comprises a list of context utterances, a list of context speakers, a response to the context, the response speaker and the persona of the response speaker.
An example from PEC looks as follows:
{'context': ['found out this morning i got a job promotion ! ! !'],
'context_speakers': ['HeWentToJared91'],
'personas': [
"i ca n't stand working in the ugli .",
'i ’ve always liked my eyes except for the fact that they ca n’t shoot lasers',
'i feel really bad about myself as a person right now , and i could really use a hand .',
'i drank a coffee , and it just made me feel even more exhausted .',
'i want a natsuki t shirt',
"i 've dealt with depression in the past .",
'i love red dead 2'],
'response': "you look like a nice person ! we 're proud of you , and i bet you earned that promotion !",
'response_speaker': 'tylock'}
Data Fields
context
: a list of strings, each string denotes a context utterance.context_speakers
: a list of strings, each string denotes a speaker.response
: a string denoting the response to thecontext
.response_speaker
: a string denoting the speaker ofresponse
.personas
: a list of strings, each string denotes a persona sentence ofresponse_speaker
.
Data Splits
The data is split into a training, validation and test set for each of the three domains. Note that the all domain is the concatenation of the happy and offmychest domains.
domain | train | validation | test |
---|---|---|---|
happy | 157195 | 19829 | 22730 |
offmychest | 123968 | 16004 | 15324 |
all | 281163 | 35833 | 38054 |
Dataset Creation
Curation Rationale
PEC was built to provide a testbed for machines to learn persona-based empathetic responding. In our empirical analysis, we found that different personas have different styles of empathetic responding. This dataset can also be used to investigate the link between persona and empathy in human conversations. According to our human assessment, the conversations on the happy and offmychest subreddits are significantly more empathetic than casual conversations.
Source Data
Initial Data Collection and Normalization
The data was obtained via the pushshift API via Google BigQuery.
Who are the source language producers?
The language producers are users of the r/happy, and r/offmychest subreddits between 2012 and 2020. No further demographic information was available from the data source.
Annotations
Annotation process
The dataset does not contain any additional annotations.
Who are the annotators?
[More Information Needed]
Personal and Sensitive Information
The dataset includes the speaker IDs of users on happy and offmychest subreddits.
Considerations for Using the Data
Social Impact of Dataset
The purpose of this dataset is to help develop more personalised and empathetic conversational systems, which is an important milestone towards truly human-like conversational agents.
Discussion of Biases
[More Information Needed]
Other Known Limitations
A small portion of the dataset has the issues of sexism, hate, and harassment. The persona sentences are noisy.
Additional Information
Dataset Curators
The dataset was initially created by Peixiang Zhong, Chen Zhang, Hao Wang, Yong Liu, and Chunyan Miao, jointly done at Nanyang Technological University and Alibaba Group.
Licensing Information
The licensing status of the dataset hinges on the legal status of the Pushshift.io data which is unclear.
Citation Information
@inproceedings{zhong-etal-2020-towards,
title = "Towards Persona-Based Empathetic Conversational Models",
author = "Zhong, Peixiang and
Zhang, Chen and
Wang, Hao and
Liu, Yong and
Miao, Chunyan",
booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
year = "2020",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/2020.emnlp-main.531",
pages = "6556--6566"
}
Contributions
Thanks to @zhongpeixiang for adding this dataset.
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