Dept. of Computer Sciences and CAI Laboratory, University of Texas, Austin.

In R. J. O'Brien (Ed.), Report of the twenty-second annual round table meeting on linguistics and language studies. (Monograph Series on Languages and Linguistics, No. 24.) Washington, D.C.: Georgetown University Press, 35-56.

Full text available for a fee. "The use of augmented transition network grammars for the analysis of natural language sentences is described. Structure-building actions associated with the arcs of the grammar network allow for the reordering, restructuring, and copying of constituents necessary to produce deep-structure representations of the type normally obtained from a transformational analysis, and conditions on the arcs allow for a powerful selectivity which can rule out meaningless analyses and take advantage of semantic information to guide the parsing. The advantages of this model for natural language analysis are discussed in detail and illustrated by examples. An implementation of an experimental parsing system for transition network grammars is briefly described." Communications of the ACM, Vol. 13, No. 10, October, 1970, pp. 591-606 (reprinted in RNLP: 71-88).

Kuhn (1962) has persuasively argued that science progresses by means of its paradigms--its models of the general nature of a research area--and that at the frontiers of research the primary quest is for a good paradigm. The small frontier outpost of language data processing has been characterized by an intensive seeking for a paradigm suitable to guide its researchers as they survey the complex topography of natural language structures. The earliest paradigm--one that led mechanical translators and early information retrievalists into a hopeless cul-de-sac--was that words (i.e.

A parsing algorithm which seems to be the most efficient general context-free algorithm known is described. It is similar to both Knuth's LR(k) algorithm and the familiar top-down algorithm. It has a time bound proportional to n3 (where n is the length of the string being parsed) in general; it has an n2 bound for unambiguous grammars; and it runs in linear time on a large class of grammars, which seems to include most practical context-free programming language grammars. In an empirical comparison it appears to be superior to the top-down and bottom-up algorithms studied by Griffiths and Petrick.

Note: PDF of full volume downloadable by clicking on title above (32.8 MB). Selected individual chapters available from the links below.CONTENTSINTRODUCTORY MATERIALMATHEMATICAL FOUNDATIONS1 Program scheme equivalences and second-order logic. D. C. COOPER 32 Programs and their proofs: an algebraic approach.R. M. BURSTALL and P. J. LANDIN 173 Towards the unique decomposition of graphs. C. R. SNOW andH. I. SCOINS 45THEOREM PROVING4 Advances and problems in mechanical proof procedures. D. PRAWITZ 595 Theorem-provers combining model elimination and Tesolution.D. W. LOVELAND 736 Semantic trees in automatic theorem-proving. R. KOWALSKI andP. J. HAYES 877 A machine-oriented logic incorporating the equality relation.E. E. SIBERT 1038 Paramodulation and theorem-proving in first-order theories withequality. G. ROBINSON and L. Wos 1359 Mechanizing higher-order logic. J. A. ROBINSON 151DEDUCTIVE INFORMATION RETRIEVAL10 Theorem proving and information retrieval. J. L. DARLINGTON 17311 Theorem-proving by resolution as a basis for question-answeringsystems. C. CORDELL GREEN 183MACHINE LEARNING AND HEURISTIC PROGRAMMING12 Heuristic dendral: a program for generating explanatory hypothesesin organic chemistry. B. BUCHANAN, G. SUTHERLAND andE. A. FEIGENBAUM 20913 A chess-playing program. J. J. SCOTT 25514 Analysis of the machine chess game. I. J. GOOD 26715 PROSE—Parsing Recogniser Outputting Sentences in English.D. B. VIGOR, D. URQUHART and A. WILKINSON 27116 The organization of interaction in collectives of automata. 285V. I. VARSHAVSKY COGNITIVE PROCESSES: METHODS AND MODELS17 Steps towards a model of word selection. G. R. Kiss 31518 The game of hare and hounds and the statistical study of literaryvocabulary. S. H. STOREY and M. A. MAYBREY 33719 The holophone —recent developments. D. J. WILLSHAW andH. C. LONGUET-HIGGINS 349PATTERN RECOGNITION20 Pictorial relationships — a syntactic approach. M. B. CLOWES 36121 On the construction of an efficient feature space for optical characterrecognition. A. W. M. COOMBS 38522 Linear skeletons from square cupboards. C. J. HILDITCH 403PROBLEM-ORIENTED LANGUAGES23 Absys 1: an incremental compiler for assertions; an introduction.J. M. FOSTER and E. W. ELCOCK 423PRINCIPLES FOR DESIGNING INTELLIGENT ROBOTS24 Planning and generalisation in an automaton/environment system.J. E. DORAN 43325 Freddy in toyland. R. J. POPPLESTONE 45526 Some philosophical problems from the standpoint of artificialintelligence. J. MCCARTHY and P. J. HAYES 463INDEX 505 Machine Intelligence Workshop

AN AUGMENTED STATE TRANSITION NETWORK ANALYSIS PROCEDURE Daniel G. Bobrow Bolt, Beranek and Newman, Inc. Cambridge, Massachusetts Bruce Eraser Language Research Foundation Cambridge, Massachusetts Summary A syntactic analysis procedure is described which obtains directly the deep structure information associated with an input sentence. The implementation utilizes a state transition network characterizing those linguistic facts representable in a context free form, and a number of techniques to code and derive additional linguistic information and to permit the compression of the network size, thereby allowing more efficient operation of the system. By recognizing identical constituent predictions stemming from two different analysis paths, the system determines the structure of this constituent only once. When two alternative paths through the state transition network converge to a single state at some point In the analysis, subsequent analyses are carried out only once despite the ...

Grammars or syntax specifications address themselves to the characterisation in symbolic terms of the structure of complex expressions. Two types of expression of empirical interest have been studied: sentences in English and other'natural' languages, and programs written in some high-level procedural language like ALGOL. Expressions in these languages consist of sets of elements (words and characters) coordinated with one another according to the sensorily manifest relationship'alongside', more commonly termed'followed by'.

Note: PDF of full volume downloadable by clicking on title above (26 MB). Selected individual chapters available from the links below. CONTENTSINTRODUCTION MATHEMATICAL FOUNDATIONS1 The morphology of prex—an essay in meta-algorithmics. J. LAS KS 32 Program schemata. M. S. PATE RSON 193 Language definition and compiler validation. J. J. FLORENTIN 334 Placing trees in lexicographic order. H. I.S COINS 43 THEOREM PROVING5 A new look at mathematics and its mechanization. B. M ELTZER 636 Some notes on resolution strategies. B. MELTZER 717 The generalized resolution principle. J. A. ROBINSON 778 Some tree-paring strategies for theorem proving. D.LUCKHAM 959 Automatic theorem proving with equality substitutions andmathematical induction. J. L. D ARLINGTON 113 MACHINE LEARNING AND HEURISTIC PROGRAMMING10 On representations of problems of reasoning about actions.S.AMAREL 13111 Descriptions. E.W.ELCOCK 17312 Kalah on Atlas. A.G.BELL 18113 Experiments with a pleasure-seeking automaton: J. E. DORAN 19514 Collective behaviour and control problems. V.I.VARSHAVSKY 217 MAN—MACHINE INTERACTION15 A comparison of heuristic, interactive, and unaided methods ofsolving a shortest-route problem. D.MICHIE, J. G. FLEMING andJ. V.OLDFIELD 24516 Interactive programming at Carnegie Tech. A.H.BOND 25717 Maintenance of large computer systems—the engineer's assistant.M.H.J.BAYLIS 269 COGNITIVE PROCESSES: METHODS AND MODELS18 The syntactic analysis of English by machine. J.P.THORNE,P.BRATLEY and H.DEWAR 28119 The adaptive memorization of sequences. H.C.LONOUETHIGGINSand A.ORTONY 311 PATTERN RECOGNITION20 An application of Graph Theory in pattern recognition.C.J.HILDITCH 325 PROBLEM-ORIENTED LANGUAGES21 Some semantics for data structures. D. PARK 35122 Writing search algorithms in functional form. R.M.BURSTALL 37323 Assertions: programs written without specifying unnecessaryorder. J.M.FOSTER 38724 The design philosophy of Pop-2. R.J.POPPLESTONE 393 INDEX 403 Machine Intelligence Workshop

Department of Computer Science University of Edinburgh 1. INTRODUCTION In this paper we describe a program which will assign deep and surface structure analyses to an infinite number of English sentences.1 The design of this program differs in several respects from that of other automatic parsers presently in existence. All these differences are a consequence of the particular aim we have pursued in writing the program, which represents an attempt to construct a device that will not only assign a syntactic analysis to any English sentence-that is, a record of the syntactic structure that the native speaker Perceives in any English sentence-but which also, to some extent, simulates the way in which he perceives this structure. This is not to say that the analyzer differs from others because we have based its design upon the findings of psycholinguistic experiments. For one thing very few experiments on the perception of syntactic structure have been carried out and for the most part the results have been fairly inconclusive. But it is the case that we have, as far as possible, treated the task of constructing an automatic parser as being itself a psycholinguistic experiment. That is to say, any proposal regarding the possible operation of the program has been judged (mainly as the result of introspection) according to whether or not it seemed to be consistent with human behaviour. And this has led to our incorporating certain features which are absent from other automatic parsing systems.