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Tagging Keywords in Text

In programmatic labeling, tagging keywords in text allows you to identify and label specific words or phrases that are of interest or relevance to your task or domain. Whether it's single words or multi-word expressions, keyword tagging plays a crucial role in various natural language processing (NLP) tasks.

Tagging Single Keywords

Tagging single keywords involves identifying and labeling individual words or terms in a given text. These keywords can represent important concepts, specific entities, or any other relevant information.

Here are some examples of single keywords that can be tagged:

  • Technology: Tagging the keyword "technology" to identify mentions of technological advancements or discussions.
  • Healthcare: Labeling the keyword "healthcare" to identify references to healthcare-related topics.
  • Finance: Tagging the keyword "finance" to identify mentions of financial matters or discussions.

By tagging single keywords, you can efficiently categorize and extract specific information from text data.

Tagging Multi-Word Keywords

In addition to single keywords, our platform supports tagging multi-word expressions or phrases as keywords. This allows you to capture more complex concepts or specific phrases that hold significance in your task or domain.

Here are some examples of multi-word keywords that can be tagged:

  • Artificial Intelligence: Labeling the multi-word expression "artificial intelligence" to identify mentions of AI-related discussions or applications.
  • Customer Satisfaction: Tagging the phrase "customer satisfaction" to capture references to customer experience or feedback.
  • Supply Chain Management: Labeling the multi-word expression "supply chain management" to identify discussions or information related to supply chain processes.

Tagging multi-word keywords enables you to extract more nuanced information from text, capturing specific phrases or expressions that convey meaning in your domain.