Natural Language Generation: Discourse Planning. Paul Gallagher 28 April 2005 (Material adapted from Ch. 20 of Jurafsky and Martin unless otherwise noted). Introduction. Programs that generate natural language are very common “Hello, world” (Kernighan and Ritchie)
28 April 2005
(Material adapted from Ch. 20 of Jurafsky and Martin unless otherwise noted)
(Reiter and Dale)
Knowledge Base + Communicative Goal
An NLG Reference Architecture
Natural Language Text
Adapted from Dale & Reiter. “Building Applied Natural Language Generation Systems”
Knowledge base representation of a saving procedure
(Jurafsky and Martin. Fig. 20.5)
A schema from representing procedures. Implemented as an augmented transition network (ATN).
Jurafsky and Martin. Fig 20.6
I love to collect classic
My favorite car is my 1899
However, I prefer to drive
my 1999 Toyota.
Name: Expand Purpose
(COMPETENT hearer (DO-ACTION ?action))
(c-get-all-substeps ?action ?sub-actions)
(NOT singular-list? ?sub-actions))
(COMPETENT hearer (DO-SEQUENCE ?sub-actions))
(((RST-PURPOSE (INFORM s hearer (DO ?action))) *required*))
Name: Expand Sub-Actions
(COMPETENT hearer (DO-SEQUENCE ?actions))
(foreach ?actions (RST-SEQUENCE (COMPETENT hearer (DO-ACTION ?actions))))
Jurafsky and Martin, pp. 786 and 788
The full rhetorical structure for the example text.
Jurafsky and Martin. Fig. 20.7.