  Long-term Web archives comprise Web documents gathered over longer time
periods and can easily reach hundreds of terabytes in size. Semantic
annotations such as named entities can facilitate intelligent access to the Web
archive data. However, the annotation of the entire archive content on this
scale is often infeasible. The most efficient way to access the documents
within Web archives is provided through their URLs, which are typically stored
in dedicated index files.The URLs of the archived Web documents can contain
semantic information and can offer an efficient way to obtain initial semantic
annotations for the archived documents. In this paper, we analyse the
applicability of semantic analysis techniques such as named entity extraction
to the URLs in a Web archive. We evaluate the precision of the named entity
extraction from the URLs in the Popular German Web dataset and analyse the
proportion of the archived URLs from 1,444 popular domains in the time interval
from 2000 to 2012 to which these techniques are applicable. Our results
demonstrate that named entity recognition can be successfully applied to a
large number of URLs in our Web archive and provide a good starting point to
efficiently annotate large scale collections of Web documents.
