Semantic Web: Where Are The Meaning-Enabled Authoring Tools?

ByNitin Karandikar Much has been written recently about theconcepts, approaches and applications of theSemantic Web. But there's something missing. In terms of understanding, finding and displaying content, there is no doubt that the Semantic Web is slowly becoming real (e.g. there were some great demos at arecent SDForum meet ). However, there is a gap emerging with Content Authoring tools, which have not yet made this paradigm shift.
On the one hand, most authors are comfortable with, and proficient in, desktop authoring tools such as Microsoft Word, FrontPage, Adobe GoLive and others. This is especially true for professionals and other experts who create technical reference content for web applications, such as legal references, accounting manuals or engineering documents. The current crop of authoring tools produce visually high-quality articles and web pages, but their XML creation capabilities are severely limited.
On the other hand, parsing Word documents or HTML web pages to extract meaningful XML out of them gives poor results; much of the semantic knowledge of the content is lost. There do not appear to be any popular tools that create Semantic content natively and yet are natural and easy for a content author to use.
Top-Down? Or Bottom-Up?
Of course, there are ways to get around this issue to some extent. Allowing authors or readers to add tags to articles or posts allows a measure of classification, but it does not capture the true semantic essence of the document. Automated Semantic Parsing (especially within a given domain) is on the way - a laSpock,twine andPowerset - but it is currently limited in scope and needs a lot of computing power; in addition, if we could put the proper tools in the authors' hands in the first place, extracting the semantic meaning would be so much easier.
For example, imagine that you are building an online repository of content, using paid expert authors or community collaboration, to create a large number of similar records - say, a cookbook of recipes, a stack of electrical circuit designs, or something similar. Naturally, you would want to create domain-specific semantic knowledge of your stack at the same time, so that you can classify and search for content in a variety of ways, including by using intelligent queries.
Ideally, the authors would create the content as meaningful XML text, so that parsing the semantics would be much easier. A side benefit is that this content can then be easily published in a variety of ways and there would be SEO benefits as well, if search engines could understand it more easily. But tools that create such XML, and yet are natural and easy for authors to use, don't appear to be on their way; and the creation of a custom tool for each individual domain seems a difficult and expensive proposition.