Hello Brothers,

recently we acquired an interesting book Foundations of Statistical Natural Language Processing. This is supposed to be the current State-Of-The-Art reference book for statistical NLP. I'd like to cite from chapter 4 (Corpus-Based Work), Section 4.1.3 (Software), especially the paragraph about Programming languages (page 121):

Most Statistical NLP work is currently done in C/C++. The need to deal
with large amounts of data collection and processing from large texts
means that the efficiency gains of coding in a language like C/C++ are
generally worth it. But for a lot of the ancillary processing of text, there
are many other languages which may be more economical with human
labor. Many people use Perl for general text preparation and reformatting.
Its integration of regular expressions into the language syntax is
particularly powerful. In general, interpreted languages are faster for
these kinds of tasks than writing everything in C. Old timers might still
use awk rather than Perl - even though what you can do with it is rather
more limited. Another choice, better liked by programmingpurists is
Python, but using regular expressionsin Python just is not as easy as
Perl. One of the authors still makes considerable use of Prolog. The built-
in database facilities and easy handling of complicated data structures
makes Prolog excel for some tasks, but again, lacks the easy access to
regular expressions available in Perl. [...]

So it seems, we're not driving that bad with Perl as our choice. :-)

Bye
 PetaMem

In reply to Statistical NLP by PetaMem

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