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Re: Re: Statistical NLP

by Hanamaki (Chaplain)
on Aug 01, 2002 at 11:32 UTC ( #186734=note: print w/replies, xml ) Need Help??

in reply to Re: Statistical NLP
in thread Statistical NLP

I can't help but think that Perl also appeals to linguists because Larry Wall consciously incorporated elements of human languages into Perl itself:...

While I cannot give any proof that your opionion is FALSE, I do not think you are right in this case. If the incorporation of elements of human languages appeals to some group, it will should rather appeal to the set of humans in general, than to its subset of linguists. Considering the extensive use of the zero pronoun ($_), Perl could be viewed as more appealing to native speakers of Japanese than to Anglosaxons. No, I don't believe this, but if someone has empirical data about it, I may chance my mind.

A more functional approach would be to ask what Perl gives to Linguists to make there job easier. Since you can easily built regular grammars (Chomsky Hierarchy Type 3 Grammars) with the regular part of Perl's unregular expressions Perl is a good tool to implement Type 3 grammars and/or test some theories. If you look further into Natural Language Processing you will see that finite state technologies are wildly applied and got some popularity in the field. Implementing finite state automata (m//) and finite state transducter (s///) in Perl is pretty easy. While you may port some really huge automata to C or whatever for efficiency Perl should be good enough for experimenting and building smaller automata. So for some kind of theroretical linguistics Perl is a easy to use tool, and therfore popular (at least among students). While you can built context-free Grammars (Chomsky Type 2) with Perl or Perl parser modules, a linguist needing this kind of grammar may leave Perl and look for some other programming language. Probably Perl isn't that popular in the field of Semantics as well. Here Prolog seems to rule.

As we know Perl is a pretty good language for text processing/ matching. Aka a good helper programming language for corpus linguistics, statistical NLP, data preparation, etc. pp.


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