We introduce a set of biologically and computationally motivated design choices for modeling the learning of language, or of other types of sequential, hierarchically structured experience and behavior, and describe an implemented system that conforms to these choices and is capable of unsupervised learning from raw natural-language corpora. Given…

This sourcebook is intended to provide researchers and users of natural language computer systems with a classification scheme to describe language-related problems associated with such systems. Methods from the disciplines of artificial intelligence (AI), education, linguistics, psychology, anthropology, and psychometrics were applied in an…

A computer-based artificial neural network (ANN) that learns to classify sentences in a text as important or unimportant is described. The program is designed to select the sentences that are important enough to be included in composition of an abstract of the text. The ANN is embedded in a conventional symbolic environment consisting of…

Consisting of two separate papers, "Representational Issues in Systemic Functional Grammar," by Christian Matthiessen and "Systemic Grammar and Functional Unification Grammar," by Robert Kasper, this document deals with systemic aspects of natural language processing and linguistic theory and with computational applications of…

Taking the lexicogrammatical resources (i.e. the vocabulary and syntax) of English as a starting point, this report explores the demands those resources put on the design of the part of a text generation system that supports the process of lexicogrammatical expression. The first section of the report notes that a reason for using the lexicogrammar…