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Mixture of Conversations Dataset
Data Science and Analytics
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About
Conversational data is presented as a collection of dialogues sourced from varied origins. This resource, titled DistillChat v1: Mixture of Conversations, represents each dialogue as a list of messages (strings). It provides a valuable foundation for the study and analysis of conversations across different contexts. The included dialogues exhibit significant diversity, encompassing a broad array of topics and scenarios, such as casual exchanges between friends, customer support interactions, and discussions from online forums. The material is structured to capture the natural flow of conversation and includes instances of both structured and unstructured dialogues.
Columns
The primary data file,
train.csv, contains 168k valid records across 4 columns:- id: A numerical identifier for each entry. This field is 100% valid, with approximately 86.6k unique values.
- conversations: A list representing the messages exchanged between participants in a conversation. Each individual message is provided as a string within the list. This field is 100% valid, featuring about 86.2k unique lists of messages.
- dataset: The name or identifier of the specific source dataset that the conversations belong to. This string field is 100% valid, containing 15 unique sources, with 'ultrachat_200k' being the most frequently occurring identifier (12%).
- model: The name or identifier of the model that generated or was responsible for the conversations. This field is 100% missing (0% valid records).
Distribution
The material is distributed as a single CSV file,
train.csv, which is 460.63 MB in size. The dataset provides 168k valid records across the primary fields (id, conversations, and dataset). All fields, except for the model identifier field, exhibit 100% validity. The expected update frequency is Never.Usage
This resource is suited for various Natural Language Processing (NLP) applications. It is specifically useful for training chatbot systems, dialogue generation models, sentiment analysis algorithms, and other conversational Artificial Intelligence (AI) applications. It can be leveraged for research to analyse patterns in human communication, study language understanding capabilities, or test dialogue strategies. Additionally, it supports training customer support models to effectively handle diverse customer queries and provide appropriate responses.
Coverage
The scope includes conversational data points drawn from multiple domains and platforms, ensuring a rich collection for analysis. The material covers wide-ranging scenarios, from casual social chats to formal customer support interactions. Each conversation entry includes associated metadata detailing the originating dataset and the identifier of the model that generated it.
License
CC0 1.0 Universal (CC0 1.0) - Public Domain
Who Can Use It
The dataset is intended for researchers, practitioners, developers, and enthusiasts focused on conversational AI. It is highly valuable for those working on text classification, intent recognition, sentiment analysis, language modeling, and studies related to human-computer interaction. The material has a maximum usability rating of 10.00.
Dataset Name Suggestions
- DistillChat v1: Mixture of Conversations
- Conversational Dataset with Diverse Sources
- Mixture of Conversations Dataset
Attributes
Original Data Source: Mixture of Conversations Dataset
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