Short answer
A Semantic Map organizes your Index’s key terms into logical categories, improving the accuracy and clarity of AI-powered searches and answers.
Full explanation
A Semantic Map is a structured list of important terms for a specific Index, grouped into categories. It uses AskTuring’s patented technology to enhance how the AI interprets and searches your documents.
Each Semantic Map typically has 4–10 categories. These are logical groupings of terms—such as “Policies,” “Procedures,” or “Key Forms”—that make sense for your documents. You should also create one “catch-all” category called something like “General Terms” to hold anything that doesn’t fit neatly into the other groups.
By mapping out terms, you help AskTuring better understand the meaning and context in your documents, resulting in more accurate searches and clearer responses.
Example:
If your Index contains training manuals, you might have categories for “Safety Procedures,” “Equipment Names,” “Regulations,” and “General Terms.” This structure lets you target searches more precisely and quickly find the right information.
Tips
Keep category names clear and consistent.
Review and update your Semantic Map as new documents are added.
Use “General Terms” as a flexible space for uncategorized terms.