Imagine your search engine understands that "Barcelona" is a city in "Europe",

it can answer a search query on "IT Companies in Europe" with

a link to a document about Yahoo Office in Barcelona,

although the exact words "Barcelona" or "Yahoo" never occur in your search query.

It helps to bridge the ambiguity of the natural language

when expressing notions and their computational representation in a formal language.

By telling a computer

how data items are related and

how these relations can be evaluated automatically,

it becomes possible to process complex filter and search operations.

Tagging refers to speed up searching and helps you find relevant and precise information.

Semantic Annotation goes one level deeper:

---- enriches the unstructured or semi-structured data with

a context that is further linked to the structured knowledge of a domain.

---- allows results that are not explicitly related to the original search.

So, if tagging is about promptly finding the most relevant result,

semantic annotation adds diversity and richness to the process.

Annotation, or tagging, is about attaching names, attributes, comments, descriptions, etc.

to a document or to a selected part in a text.

It provides additional information (metadata) about an existing piece of data.