Entity Extraction Results Summary

Your submitted URL or content is analyzed with TextRazor to extract entities, which are further enriched with data from DBpedia. Entities are key concepts, names, or terms identified within the content. The results are displayed as follows:

• 1. Highlighted Entities

  Entities are visually marked using different shades to denote their relevance scores:

  • Darker shades represent entities with higher relevance.
  • Lighter shades indicate entities with lower relevance.

• 2. Filter by Relevance Score

  Use the Relevance Score Filter to focus on entities within a specific relevance range:

  • Adjust the range slider to set the minimum and maximum relevance scores.
  • Entities with relevance scores outside the selected range will not be highlighted.
  • This allows you to reduce visual clutter and focus on the most significant entities in the content.

• 3. Shading Options

  Customize the shading colors to match your preferences or analysis needs. For example, switch between color themes like yellow, orange, teal, and more.

• 4. Entity Details

  Each entity includes detailed information, such as:

  • Entity Name: The identified term (e.g., “Heart” or “Coronary Artery Disease”).
  • Relevance Score: Indicates how relevant the entity is to the overall content.
  • Confidence Score: Reflects the accuracy of the extraction.
  • Entity Type: Categorization of the entity (e.g., “Disease” or “AnatomicalStructure”).
  • Knowledge Base Links: Links to related Wikipedia or DBpedia pages.
  • Statistical Insights: Including the number of Wikipedia inlinks and DBpedia similarity scores.

• 5. Markup View

  The content is returned as HTML markup with entities wrapped in highlighted tags. You can interact with or download the results directly.

• 6. Export Option

  Export all extracted entities and their associated statistics into a CSV file for further analysis.