MapReduce: : Simplified Data Processing on Large Clusters
http://www.usenix.org/events/osdi04/tech/dean.html
http://people.cs.vt.edu/~gback/MapReduce.pdf

Machine Translation – destined to be damned with faint praise. Chinese isn’t hard to translate; most of the relative difficulty of the language lies in learning the characters. Japanese and Korean have a much more unique grammatical structure. No idea on Arabic.

Named Entity Extraction (as opposed to unnamed entities? nouns?) – This sounds like Google Sets. IIRC they were scanning text for list-type noun phrases (eg North, South, East and West), and building up associations from them.

Clustering – sounds like they’ve rediscovered data mining. It’s not clear what algorithm they’re using, but I can think of a few that might work with a large inverted index.

Your mistake is a good sample of the use of clustering (one word, several meanings). Perhaps you used Google to search “Google+cluster”, and the first result is the document you linked. But it wasn’t the “cluster” you looked for.

The document explains how the X,000 Google servers are clustered in order to run quickly and help with users’ queries.

And what Peter explained on ‘Web 2.0′ was how Google plans to cluster search results by learning the meaning of the web pages.