Openerotica/basilisk-v0.2 Conversations Dataset
Annotated Conversations from openerotica and freedom-rp
@kaggle.thedevastator_openerotica_basilisk_v0_2_conversations_dataset
About this Dataset
Openerotica/basilisk-v0.2 Conversations Dataset
openerotica/basilisk-v0.2 Conversations Dataset
Annotated Conversations from openerotica and freedom-rp
By openerotica (From Huggingface) [source]
About this dataset
The Conversations dataset is a collection of annotated conversations between participants, sourced from the openerotica and freedom-rp datasets. It is specifically designed for training conversational models. The dataset consists of two main components: conversations and train.csv.
The conversations component is represented as a list of lists, where each conversation is a sequence of messages exchanged between participants. Each message includes the text content and the role of the participant who sent it.
The train.csv file contains annotated conversations obtained from both openerotica and freedom-rp datasets. This file serves as a training resource for developing conversational models. It offers valuable insights into participant interactions, providing context and understanding for building effective conversation systems.
By utilizing this dataset, developers can analyze conversational patterns, study language use in dialogue scenarios, and train AI models to engage in human-like conversations. The annotations in these conversations aid in labeling data for supervised learning tasks related to natural language understanding (NLU) or generative chatbots.
In summary, this Conversations dataset presents an extensive collection of annotated exchanges extracted from openerotica and freedom-rp datasets. It offers abundant opportunities to enhance research on conversational AI systems by facilitating the development and evaluation of advanced dialogue models using real-world data examples
How to use the dataset
How to Use the Conversations Dataset - openerotica/basilisk-v0.2
The openerotica/basilisk-v0.2 dataset is a collection of annotated conversations from the openerotica and freedom-rp datasets. These conversations are represented as lists of messages exchanged between participants, where each message includes the text content and the role of the participant who sent it.
To effectively use this dataset for your analysis or model training, here's a guide on how you can utilize it:
Understanding Conversation Structure: The main feature in this dataset is the conversations column, which represents a conversation as a list of messages exchanged between participants. Each message includes two fields:
- Text Content: This field contains the text content of a particular message within a conversation.
- Role of Participant: This field denotes whether each message was sent by a specific participant role (e.g., user, assistant) in that conversation.
Extracting Conversations: Iterate through each row in train.csv, accessing and parsing individual conversation entries from within those rows' conversations column. Each entry will be represented as its own list containing multiple messages.
Analyzing Message Content: Explore and analyze various aspects of messages within each conversation to gain insights related to natural language processing (NLP), sentiment analysis, or any other NLP-related task you're interested in.
Training Models: If your objective is to train conversational models using this dataset, you can utilize techniques such as sequence-to-sequence modeling, chatbot training frameworks (like Transformers), or any other relevant approach. Consider using the conversations as training data for these models, with message content serving as inputs and participant roles guiding the desired output structure.
Preprocessing and Cleaning: Depending on your specific goals and tasks, you may need to preprocess and clean the text data. Common preprocessing steps include removing stop words, tokenization, stemming/lemmatization, or handling special characters.
Exploratory Data Analysis (EDA): Before starting any modeling tasks or analysis, it's crucial to perform an exploratory data analysis on this dataset. This includes analyzing conversation lengths, frequency of participants' roles, most common words/phrases used
Research Ideas
- Training conversational AI models: This dataset can be used to train machine learning models for generating realistic, engaging and contextually relevant conversations. The annotated conversations provide valuable examples that can help the model learn the nuances of natural language conversation.
- Chatbot development: The dataset can be used to develop chatbots or virtual assistants that can engage in meaningful and interactive conversations with users. By training the chatbot on this dataset, it can learn how to respond appropriately based on user messages and maintain a coherent conversation flow.
- Language generation research: Researchers in the field of natural language processing (NLP) and computational linguistics can use this dataset for studying language generation techniques. They can analyze the patterns, coherence, and contextuality of conversations in order to improve techniques for generating human-like text responses in conversational AI systems
Acknowledgements
If you use this dataset in your research, please credit the original authors.
Data Source
License
License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.
Columns
File: train.csv
| Column name | Description |
|---|---|
| conversations | A list of messages exchanged between participants in a conversation. Each message includes the text content and the role or identity of the participant who sent the message. (List of strings) |
Acknowledgements
If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit openerotica (From Huggingface).