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Question Decomposition Meaning Dataset
Data Science and Analytics
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About
Welcome to BreakData, an innovative dataset designed for exploring language understanding [1]. This dataset provides a wealth of information concerning question decomposition, operators, splits, sources, and allowed tokens, enabling precise question answering [1]. It offers deep insights into human language comprehension and interpretation, proving highly valuable for researchers developing sophisticated AI technologies [1]. The goal of BreakData is to facilitate the development of advanced natural language processing (NLP) models, applicable in various areas such as automated customer support, healthcare chatbots, or automated marketing campaigns [1].
Columns
Based on the
QDMR Lexicon: Source and Allowed Tokens file, the dataset includes the following columns:- source: This string column indicates the origin of the question [2].
- allowed_tokens: This string column specifies the tokens permitted for the question [2].
The dataset also comprises other files, such as QDMR files which include questions or statements from common domains like healthcare or banking, requiring interpretation based on a series of operators [3]. These files necessitate the identification of keywords, entities (e.g., time references, monetary amounts, Boolean values), and relationships between them [3]. Additionally, LogicalForms files contain logical forms that serve as building blocks for linking ideas across different sets of incoming variables [3].
Distribution
The BreakData dataset is typically provided in CSV format [1, 4]. It is structured into nine distinct files, which include
QDMR_train.csv, QDMR_validation.csv, QDMR-highlevel_train.csv, QDMR-highlevel_test.csv, logicalforms_train.csv, logicalforms_validation.csv, QDMRlexicon_train.csv, QDMRLexicon_test.csv, and QDHMLexiconHighLevelTest.csv [1]. While the dataset's structure is clear, specific numbers for rows or records within each file are not detailed in the provided information. The current version of the dataset is 1.0 [5].Usage
This dataset presents an excellent opportunity to explore and comprehend the intricacies of language understanding [1]. It is ideal for training models for a variety of natural language processing (NLP) activities, including:
- Question answering systems [1].
- Text analytics [1].
- Automated dialogue systems [1].
- Developing advanced NLP models to analyse questions using decompositions, operators, and splits [6].
- Training machine learning algorithms to predict the semantic meaning of questions based on their decomposition and split [6].
- Conducting text analytics by utilising the allowed tokens dataset to map how people communicate specific concepts across different contexts or topics [6].
- Optimising machine decisions for human-like interactions, leading to improved decision-making in applications like automated customer support, healthcare advice, and marketing campaigns [1, 3].
Coverage
The BreakData dataset covers a global region [5]. Its content is drawn from common domains such as healthcare and banking, featuring questions and statements that require linguistic analysis [1, 3]. There are no specific notes on time range or demographic scope beyond these general domains.
License
CC0
Who Can Use It
This dataset is primarily intended for:
- Researchers developing sophisticated models to advance AI technologies [1].
- Data scientists and AI/ML engineers looking to train models for natural language understanding tasks [1].
- Those interested in analysing existing questions or commands with accurate decompositions and operators [1].
- Developers of machine learning models powered by NLP for seamless inference and improved results in customer engagement [3].
Dataset Name Suggestions
- BreakData Language Decomposition
- Question Decomposition Meaning Dataset
- NLP Language Understanding Hub
- Semantic Question Analysis Data
- BreakData NLP Foundation
Attributes
Original Data Source: Break (Question Decomposition Meaning)
QUALITY