Annotated Data Item
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An Annotated Data Item is a data element that has been labeled with metadata or additional information to provide context, meaning, or structure for machine learning and data analysis purposes.
- Context:
- It can (typically) be created during a Data Annotation Process involving a Data Annotation Team.
- It can (often) be part of a Training Data Set used for supervised learning in machine learning.
- It can (often) be used in research to provide structured and interpretable data for analysis.
- It can include various types of data, such as annotated text data, annotated image data, annotated audio data, and annotated video data.
- It can require the use of specialized Annotation Tools to ensure consistency and accuracy.
- It can be subject to a Quality Assurance process to verify the correctness of the annotations.
- It can be utilized in various applications, including natural language processing, computer vision, and speech recognition.
- It can include Metadata Tags that categorize and describe the data.
- It can be produced through a combination of manual and automated annotation methods.
- It can play a critical role in improving the performance of AI models by providing high-quality labeled data.
- It can be stored in data repositories for reuse in multiple projects and studies.
- It can involve ethical considerations, especially when dealing with sensitive or personal data.
- It can be part of datasets in various domains, such as healthcare, e-commerce, social media, and cultural heritage.
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- Example(s):
- An annotated customer review where each sentence is labeled with sentiment (positive, negative, neutral).
- An annotated medical image with regions marked for diagnosing diseases.
- An annotated speech recognition data where transcriptions are aligned with audio segments.
- An annotated video data where objects and actions are labeled frame by frame.
- An annotated legal document (such as an annotated contract) with sections highlighted for different legal concepts.
- An annotated media archive data with descriptive tags for indexing and retrieval.
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- Counter-Example(s):
- A raw data item, which has not been labeled or annotated.
- An unstructured data that lacks any metadata or context.
- A synthetic data item, which is generated rather than collected and annotated.
- See: Data Annotation Process, Machine Learning, Training Data, Annotation Tools.