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Natural Language Processing. Lecture 6 Augmented Transition Networks Reading: James Allen NLU (Chapter 4). Augmented Transition Networks. An augmented transition network (ATN) is a recursive transition network that can perform tests and take actions during arc transitions.
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Natural Language Processing Lecture 6 Augmented Transition Networks Reading: James Allen NLU (Chapter 4)
Augmented Transition Networks • An augmented transition network (ATN) is a recursive transition network that can perform tests and take actions during arc transitions. • An ATN uses a set of registers to store information. • A set of actions is defined for each arc, and the actions can look at and modify the registers. • An arc may have a test associated with it. The arc is traversed (and its action is taken) only if the test succeeds. • When a lexical arc is traversed, it is put in a special variable (*) that keeps track of the current word.
Definite Clause Grammars • An convenient abbreviated format for writing grammar rules for logic-based parsing systems • Rules can then automatically be compiled into a full database of PROLOG clauses • Omit technical arguments that can automatically be inserted by the system: – word positions and constituent spans – explicit predicates for the lexicon entries • Resulting grammar format looks something like: S(s(Np,Vp),FS) -> NP(Np,FS), VP(Vp,FS) NP(np(Art,Noun),FS) -> ART(Art,FS), N(Noun,FS) VP(vp(Verb),FS) -> V(Verb,FS)
Register Presetting Register Presetting Parameter Passing • vp:inf Mary wants to have a party. • _np_vp:inf Mary wants John to have a party. Register VFORM of VP Graph should be preset to inf