Lynne J. Cahill

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The interaction between theoretical and computational linguistics, while not often acknowledged, undoubtedly had some influence in the relative failure of the previous incarnations of Hudson's Word Grammar (also known as Dependency Grammar and Daughter-Dependency Grammar) to capture the imagination in the same way that the context-free phrase structure(More)
This paper addresses the question of whether Reiter's `Consensus NL Generation Architecture' Rei94] really exists, and if so whether it is a suitable candidate for a `reference architecture' for NLG systems. Our answer to the rst question is a tentative yes, but we are less comfortable to accept the second. In pursuit of a better understanding, we develop(More)
The great increase in work on the lexicon by computational and theoretical linguists throughout the 1980s has concerned itself, almost exclusively, with monolingual lexicons. Meanwhile, applied work on multilingual lexicons, mostly for machine translation (MT), has employed monolingual lexicons linked only at the level of semantics. In this paper, we argue(More)
We present the rags (Reference Architecture for Generation Systems) framework: a specification of an abstract Natural Language Generation (NLG) system architecture to support sharing, re-use, comparison and evaluation of NLG technologies. We argue that the evidence from a survey of actual NLG systems calls for a different emphasis in a reference proposal(More)
The RAGS proposals for generic specification of NLG systems includes a detailed account of data representation, but only an outline view of processing aspects. In this paper we introduce a modular processing architecture with a concrete implementation which aims to meet the RAGS goals of transparency and reusability. We illustrate the model with the RICHES(More)
We present the rags (Reference Architecture for Generation Systems) framework, a specification of an abstract Natural Language Generation (NLG) system architecture to support sharing, re-use, comparison and evaluation of NLG technologies. We argue that the evidence from a survey of actual NLG systems calls for a different emphasis in a reference proposal(More)
The RAGS project aims to develop a reference architecture for natural language generation, to facilitate modular development of NLG systams as well as evaluation of components, systems and algorithms. This paper gives an overview of the proposed framework, describing an abstract data model with five levels of representation: Conceptual, Semantic,(More)