Annotated Text-Item
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An Annotated Text-Item is a text item that is an annotated artifact (with annotation markup).
- AKA: Marked-up Text, Tagged Text Item, Enriched Text.
- Context:
- It can typically contain Annotation Metadata through embedded markup or external reference systems.
- It can typically preserve Original Text Content alongside annotation layers.
- It can typically support Multiple Annotation Types through annotation schemas.
- It can typically enable Text Analysis through structured annotations.
- It can typically facilitate Content Classification through categorical annotations.
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- It can often be created within a Text Annotation Project (or text annotation program).
- It can often serve as training data for natural language processing models.
- It can often follow Annotation Guidelines for consistency and quality control.
- It can often include Confidence Scores for annotation reliability.
- It can often undergo Inter-Annotator Agreement Assessment for quality verification.
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- It can range from being an Externally Annotated Text Item (with annotations about the entire text item) to being an Internally Annotated Text Item (with annotations about internal text item components).
- It can range from being a Semantically Annotated Text Item to being a Syntactically Annotated Text Item.
- It can range from being an Annotated Sentence to being an Annotated Text Document.
- It can range from being a Human Annotated Text Item to being a Machine Annotated Text Item, depending on its annotation source.
- It can range from being a Lightly Annotated Text Item to being a Densely Annotated Text Item, depending on its annotation density.
- It can range from being a Single-Layer Annotated Text to being a Multi-Layer Annotated Text, depending on its annotation complexity.
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- It can be an output of a Text Annotation Task.
- It can be an input to an Annotated Text Repair Task, Annotated Text Editing Task, Text Mining Process, or Annotation Verification Process.
- It can be a member of an Annotated Corpora.
- It can be used for Information Extraction from unstructured text.
- It can provide Linguistic Context through contextual annotations.
- It can support Cross-Document Reference through entity linking annotations.
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- Examples:
- Annotated Text Document Types, such as:
- Linguistic Annotations, such as:
- Semantic Annotations, such as:
- Structural Annotations, such as:
- Specific Text Item Types, such as:
- CPROD1 Annotated Textitem for product classification.
- Annotated Text Sentence for sentence-level analysis.
- Annotated Mention for reference identification.
- Annotated Product Offering Title for e-commerce categorization.
- Word Mention Annotated Text Item for lexical analysis.
- Tokenized Text Item for text processing.
- Annotated Contract Provision Sentence for legal analysis.
- Revision-Tracking Annotations, such as:
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- Annotated Text Document Types, such as:
- Counter-Examples:
- Unannotated Text Item, which lacks any markup or annotation layers.
- Annotated DNA Sequence, which applies annotation to genetic material rather than linguistic content.
- Image Annotation, which applies markup to visual content rather than text.
- Raw Text Corpus, which contains text collections without structured annotations.
- Binary Document Format, which stores documents in non-text formats without human-readable annotations.
- See: Natural Language Processing, Markup Language, Annotated Written Artifact, Text Corpus, Linguistic Annotation, Document Markup System, Collaborative Text Editing, Redlined Annotated Text.