Artificial Intelligence
Data Labelling
Plain English
Adding labels to glossaryDataData is raw, uninterpreted information collected and stored so it can be analysed, processed, or used to inform decisions. On its own it carries no meaning; context and interpretation are what make it useful.Open glossary term so machines can understand it.
Definition
glossaryDataData is raw, uninterpreted information collected and stored so it can be analysed, processed, or used to inform decisions. On its own it carries no meaning; context and interpretation are what make it useful.Open glossary term glossaryLabellingLabelling is the practice of naming content, categories, and interface elements in a way that is clear and meaningful to users. It directly affects how users understand and navigate a product.Open glossary term is the glossaryProcessA process is a defined sequence of steps used to achieve a specific outcome.Open glossary term of tagging data with meaningful labels so it can be used for training machine learning models.
In practice
Used in AI glossarySystemA system is a collection of interconnected components that work together to achieve a specific function or outcome.Open glossary term to classify images, text, or other glossaryDataData is raw, uninterpreted information collected and stored so it can be analysed, processed, or used to inform decisions. On its own it carries no meaning; context and interpretation are what make it useful.Open glossary term types for supervised learning.
In context
It is where quality is actually determined, and it is usually the least resourced part of a project. Inconsistent labels teach the glossaryModelA model is a system or representation used to process data and generate outputs, often trained to perform specific tasks.Open glossary term to be inconsistent.
The reality
Poor glossaryLabellingLabelling is the practice of naming content, categories, and interface elements in a way that is clear and meaningful to users. It directly affects how users understand and navigate a product.Open glossary term glossaryLeadA lead is a potential customer who has shown interest in a product or service, typically by providing contact information or engaging with content.Open glossary term to poor glossaryModelA model is a system or representation used to process data and generate outputs, often trained to perform specific tasks.Open glossary term performance and unreliable outputs.
Compared with
Data Labelling vs Data Enrichment
glossaryLabellingLabelling is the practice of naming content, categories, and interface elements in a way that is clear and meaningful to users. It directly affects how users understand and navigate a product.Open glossary term adds the target, the answer a glossaryModelA model is a system or representation used to process data and generate outputs, often trained to perform specific tasks.Open glossary term is trained to predict. Enrichment adds glossaryContextContext is the set of surrounding conditions that shape how someone behaves and decides, including their goal, their environment, their time pressure, and what happened immediately before. The same action can mean different things in different contexts.Open glossary term and attributes that make records more useful. Labelling serves training; enrichment serves both training and analysis.
FAQ
Common questions
A few practical answers to the questions that usually come up around this term.
What is data labelling?
It is glossaryTaggingTagging is the process of assigning keywords or labels to content to make it easier to organise, filter, and retrieve. Tags are often flexible and non-hierarchical compared to categories.Open glossary term glossaryDataData is raw, uninterpreted information collected and stored so it can be analysed, processed, or used to inform decisions. On its own it carries no meaning; context and interpretation are what make it useful.Open glossary term so it can be used in glossaryMachine Learning (ML)Machine Learning is a subset of AI that enables systems to learn from data and improve performance without being explicitly programmed.Open glossary term.
Why is data labelling important?
It directly affects glossaryModel AccuracyModel accuracy measures how often a model produces correct or expected outputs compared to known outcomes.Open glossary term.
What types of data are labelled?
Images, text, audio, and glossaryStructured DataStructured data is a standardised format used to organise and label content so it can be easily understood by search engines and AI systems.Open glossary term.
What happens with poor labelling?
glossaryModelA model is a system or representation used to process data and generate outputs, often trained to perform specific tasks.Open glossary term produce inaccurate results.
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