One approach to this more general problem , taken by the ` Nitrogen ' generator ( Langkilde and Knight , 1998a ; Langkilde and Knight , 1998b ) , takes advantage of standard statistical techniques by generating a lattice of all possible strings given a semantic representation as input and selecting the most likely output using a bigram language model .
generation that exploits corpusbased statistical knowledge
Irene Langkilde Kevin Knight
The problem of generating ordered sequences of adjectives is an instance of the more general problem of selecting among a number of possible outputs from a natural language generation system . One approach to this more general problem , taken by the ` Nitrogen ' generator ( Langkilde and Knight , 1998a ; Langkilde and Knight , 1998b ) , takes advantage of standard statistical techniques by generating a lattice of all possible strings given a semantic representation as input and selecting the most likely output using a bigram language model . Langkilde and Knight report that this strategy yields good results for problems like generating verb/object collocations and for selecting the correct morphological form of a word .
One approach to this more general problem , taken by the ` Nitrogen ' generator ( @@CITATIONa ; Langkilde and Knight , 1998b ) , takes advantage of standard statistical techniques by generating a lattice of all possible strings given a semantic representation as input and selecting the most likely output using a bigram language model .