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matching time of the re-write rules’ left part with sentential representation (in
top-down parsing) will be significantly large. An alternative approach to
parsing is to employ augmented transition networks that can define context
sensitive languages, but is more powerful than the context sensitive grammar.
18.3 Augmented Transition Network Parsers
Augmented transition networks (ATN) [6] extend transition networks by
attaching procedures to the arcs of the networks. When an arc is traversed, the
ATN parser executes the procedure, attached to that arc. These procedures i)
assign values to grammatical features, and ii) check whether the number or
person (1 st , 2 nd , 3 rd ) conditions are satisfied and accordingly allow or fail a
transition. For instance, the ATN that may be employed for parsing part of the
sentence ‘the boy’ is presented below. Suppose the grammatical
characteristics or features of the words ‘NP’, ‘the’ and ‘boy’ are available in a
data dictionary, as shown in fig.18.9. Also assume that the procedures are
attached to the arcs of the article and noun, as described below.
NP:
the:
boy:
DET Noun Number
(b)
(c)
Fig. 18.9: The grammatical characteristics of the word (a) NP, (b) the
and (c) boy, represented by structures.
(a)
Part of Speech Root Number
ART the Singular/
Plural
Part of Speech Root Number
N boy Singular
Now, for parsing the string sequence: ‘the boy’, suppose we use the
ATN for NP. So, at state S0 of NP, it first assigns ART:= the and checks
whether the part-of-speech = ART. If yes, it assigns NP.DET:=ART;
otherwise it fails and the control returns to wherefrom it was called.