In knowledge-based natural language generation, issues of formal knowledge representation meet with the linguistic problems of choosing the most appropriate verbalization in a particular situation of utterance.
<em>Lexical Semantics and Knowledge Representation in</em> <em>Multilingual Text Generation</em> presents a new approach to systematically linking the realms of lexical semantics and knowledge
represented in a description logic. For language generation from such abstract representations, lexicalization is taken as the central step: when choosing words that cover the various parts of the content representation,
the principal decisions on conveying the intended meaning are made. A preference mechanism is used to construct the utterance that is best tailored to parameters representing the context. <br/> <em>Lexical
Semantics and Knowledge Representation in Multilingual Text</em> <em>Generation</em> develops the means for systematically deriving a set of paraphrases from the same underlying representation with the
emphasis on events and verb meaning. Furthermore, the same mapping mechanism is used to achieve multilingual generation: English and German output are produced in parallel, on the basis of an adequate division between
language-neutral and language-specific (lexical and grammatical) knowledge. <br/> <em>Lexical Semantics and Knowledge Representation in Multilingual Text</em> <em>Generation</em> provides
detailed insights into designing the representations and organizing the generation process. Readers with a background in artificial intelligence, cognitive science, knowledge representation, linguistics, or natural language
processing will find a model of language production that can be adapted to a variety of purposes.