We will use the machinery of computational linguistics to explore our thesis.
The following development may thus be used as the reference implementation of a core computational linguistics toolkit, dealing with lexical, phonological and morphological aspects.
The relevant scientific results in this case are the outputs of computational linguistics, natural language processing and artificial intelligence in general.
In the natural language processing and computational linguistics literature, there is a definite bias toward preferring 'theoretical' solutions.
Moreover, the idea to apply one-sided sampling, in order to balance the noisy dataset, on a computational linguistics task is novel.
Concerning this observation, one must take into account that considerations with respect to (inherent) ambiguity in computational linguistics differ from those in formal language theory.
Engineering-oriented computational linguistics is the study of methods for the construction or improvement of useful artifacts that manipulate natural language.
Automating the use of information in natural language format requires that computers understand language, and this involves problems studied by the computational linguistics community.
