This article discusses ways of semantic processing in a search engine. Major search engines have one main type of result – a list of links to matching Web sources. There are many enhancements on top of it, but the core premise remains the same: a search result consists of a set of individual pages. The user is expected to drill down into individual sources. An alternative type of result is suggested: an essay compiled of a number of relevant and ordered sentences. The search engine in this case parses Web sources, understands their semantics, and creates an overall summary of the topic. The idea is to save the user time by providing a quick overview of the topic. A Web sentiment analysis application based on semantic analysis is introduced.