Nicolov, Nicolas N.

2019-02-15T14:15:05Z

2019-02-15T14:15:05Z

1999

This thesis is on Natural Language Generation. It describes a linguistic realisation system that translates the semantic information encoded in a conceptual graph into an English language sentence. The use of a non-hierarchically structured semantic representation (conceptual graphs) and an approximate matching between semantic structures allows us to investigate a more general version of the sentence generation problem where one is not pre-committed to a choice of the syntactically prominent elements in the initial semantics. We show clearly how the semantic structure is declaratively related to linguistically motivated syntactic representation — we use D-Tree Grammars which stem from work on Tree-Adjoining Grammars. The declarative specification of the mapping between semantics and syntax allows for different processing strategies to be exploited. A number of generation strategies have been considered: a pure topdown strategy and a chart-based generation technique which allows partially successful computations to be reused in other branches of the search space. Having a generator with increased paraphrasing power as a consequence of using non-hierarchical input and approximate matching raises the issue whether certain 'better' paraphrases can be generated before others. We investigate preference-based processing in the context of generation.

http://hdl.handle.net/1842/33393

The University of Edinburgh

Annexe Thesis Digitisation Project 2019 Block 22

Already catalogued

Approximate text generation from non-hierarchical representations in a declarative framework

Thesis or Dissertation

Doctoral

PhD Doctor of Philosophy