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esource and the access to the resource. For this reason, these resources will remain
unexplored, even if prices are modest. Although ELRA and LDC have their merits, for
small languages, better solutions are available for the hosting of data (cf. Streiter
2005).
Project Gutenberg provides structured access to its 16,000 documents (comprising
about thirty languages) through an XML-RDF. Unfortunately, information characterising
text T1 as translation of T2 is still not provided, that is, although parallel corpora are
implicitly present, they are not identifiable as such. In theory, the documents of
Project Gutenberg could be used to build up corpora in XNLRDF. Such a copying of
resources, however, might only be justifiable for writing systems for which little corpus
material is available. More important might be a mapping from the writing system of
XNLRDF to the documents of Project Gutenberg, thus translating the available XML-
RDF in terms of XNLRDF.
Free monolingual and parallel corpora are available at a great number of sites,
most prominently at http://www.unhchr.ch/udhr/navigate/alpha.htm (Universal
Declaration of Human Rights in 330 languages), http://www.translatum.gr/bible/
download.htm (The Bible), and The European Parliament Proceedings Parallel Corpus
(http://people.csail.mit.edu/koehn/ publications/europarl), among others. Those
documents that support otherwise underrepresented writing systems will be integrated
into XNLRDF in the form of corpora.
The Wikipedia project is interesting for XNLRDF for a number of reasons. First,
it provides documents that can be used to build corpora without infringing upon
copyrights. Second, as the Wikipedia is available in more than one hundred languages,
thousands of quasi-parallel texts become accessible. Third, the model of cooperation
in Wiki projects, and the underlying software, will indicate the way XNLRDF will go.
Thus, XNLRDF will gradually enlarge the community of researchers involved to the
point that the world’s linguists will be able to collect the data they need for their
writing systems. This issue will be further discussed below.
5. Conceptual Design of XNLRDF
The purpose of XNLRDF is to find adequate NLP resources to process a text document.
To this end, the metadata of the document and the resource are matched. The better
the match, the more suitable the resource is for the processing of the document. The
metadata matched are those categories that make up the writing system.
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