Simmons, R. F.



Natural language question-answering systems: 1969

Classics

In the meantime, Chomsky (1965) devised a paradigm for linguistic analysis that includes syntactic, semantic, and phonological components to account for the generation of natural language statements. This theory can be interpreted to imply that the meaning of a sentence can be represented as a semantically interpreted deep structure--i.e, From computer science's preoccupation with formal programming languages and compilers, there emerged another paradigm. The adoption and combination of these two new paradigms have resulted in a vigorous new generation of language processing systems characterized by sophisticated linguistic and logical processing of well-defined formal data structures. These included a social-conversation machine, systems that translated from English into limited logical calculi, and programs that attempted to answer questions from English text.


Syntactic dependence and the computer generation of coherent discourse

Classics

The two primary components of the experimental computer program consisted of a phrase structure generation grammar capable of generating grammatical nonsense, and a monitoring system which would abort the generation process whenever it was apparent that the dependency structure of a sentence being generated was not in harmony with the dependency relations existing in an input source text. Potential applications include automatic kernelizing, question answering, automatic essay writing, and automatic abstracting systems. Introduction This paper sets forth the hypothesis that there is in the English language a general principle of transitivity of dependence among elements and describes an experiment in the computer generation of coherent discourse that supports the hypothesis. Given as input a set of English sentences, if we hold constant the set of vocabulary tokens and generate grammatical English statements from that vocabulary with the additional restriction that their transitive dependencies agree with those of the input text, the resulting sentences will all be truth-preserving paraphrases derived from the original set.