Local Grammar Graph

This post deals with some aspects of local grammar graph (LGG), a sequence recognizer and extraction tool. Local Grammar is developed by Maurice Gross to capture and describe a linguistic phenomena.

Some LGGs Advantageous over Regular Expression

Question. Is it the only tool? There exists another tool which is called regular expression. Many computer scientists are familiar to this term. However, there are some advantageous of LGG over regular expression. First, LGG is supported by graphic interface. It's user friendly. For someone like me who does not know much programming, it is proven to be very helpful. Check this illustration out to see how LGG looks

LGG with Output

Second, with LGG, you can give output. So here is the order. You recognize, extract, and after that give output. An example above shows you an LGG that is equipped with output. In the example, output is designed to give decription of every extracted lexicons. You can also have translation for each lexicon as long as your dictionary supports it

Three, you can describe grammar and semantic constraints more comprehensively with LGG. Let's say, you want to extract sequence of determiner plus noun. You can type DET and N (each protected by angle brackets) in regular expression and click search.

Regular Expression

But how if the sequence you want to extract is more complicated? In English, copula verbs and modal can be contracted with pronoun. For example: he's (he+is), she'd (she + could/had/would), I'm (I + am). The contraction are illustrated by the following LGG. It does not look too simple, huh.

Unitex Manual: LGG for English Contraction

This post has looked over some LGG's features in comparison to regular expression. Briefly, we can say that LGG can performed some NLP tasks which cannot be executed by regular expressions. Next posts will discuss more experiments with LGGs to carry much more specific tasks.