{ "paper_id": "J75-2012", "header": { "generated_with": "S2ORC 1.0.0", "date_generated": "2023-01-19T02:41:02.820160Z" }, "title": "New Haven, Connecticut 06520", "authors": [ { "first": "L", "middle": [], "last": "Nash-Webber", "suffix": "", "affiliation": {}, "email": "" }, { "first": "Unive", "middle": [ "'" ], "last": "Rsi T", "suffix": "", "affiliation": {}, "email": "" }, { "first": "Karlova", "middle": [], "last": "Praha", "suffix": "", "affiliation": {}, "email": "" }, { "first": "Mantaro", "middle": [ "J" ], "last": "Hashimoto", "suffix": "", "affiliation": {}, "email": "" }, { "first": "Y", "middle": [], "last": "Sabbarayalu", "suffix": "", "affiliation": { "laboratory": "STELLUNG UND AUFGABEN DER UEBRAISCHEN LTNGUISTIK I", "institution": "", "location": {} }, "email": "" }, { "first": "Masayuki", "middle": [], "last": "Nakagawa", "suffix": "", "affiliation": {}, "email": "" }, { "first": "Ryonei", "middle": [], "last": "Kagaga", "suffix": "", "affiliation": {}, "email": "" }, { "first": "Hajime", "middle": [], "last": "Hirose", "suffix": "", "affiliation": {}, "email": "" }, { "first": "Bolt", "middle": [], "last": "Beranek", "suffix": "", "affiliation": {}, "email": "" }, { "first": "Newman", "middle": [ "Inc" ], "last": "Cambridge", "suffix": "", "affiliation": {}, "email": "" }, { "first": "Roger", "middle": [ "C" ], "last": "Schank", "suffix": "", "affiliation": {}, "email": "" }, { "first": "K", "middle": [ "S" ], "last": "Fu", "suffix": "", "affiliation": {}, "email": "" }, { "first": "T", "middle": [ "L" ], "last": "Booth", "suffix": "", "affiliation": {}, "email": "" }, { "first": "Paul", "middle": [ "L" ], "last": "Garvin", "suffix": "", "affiliation": {}, "email": "" }, { "first": "Stephen", "middle": [ "E" ], "last": "Palmer", "suffix": "", "affiliation": {}, "email": "" }, { "first": "Cora", "middle": [ "Angier" ], "last": "Sowa", "suffix": "", "affiliation": {}, "email": "" }, { "first": "John", "middle": [ "E" ], "last": "Sowa", "suffix": "", "affiliation": {}, "email": "" } ], "year": "", "venue": null, "identifiers": {}, "abstract": "Acquaints speech researchers i n the s t a t e of the a r t i n the conceptual development o f , and the new perspectives they place on, parsing, syntax and semantic i n t e r p r e t a t i o n. Includes the Chomsky hierarchy of grammar models, n0.n-determinism i n parsing and i t s implemen&ation i n e i t h e r backtrdcking or multiple in4ependent a l t e r n a t i v e s , predictive vs. non-predictive parsing, word l a t t i c e s and chart parsing, Early's algorithm, t r a n s i t i o n network grammars, transfornational grammars and augmented t r a n s i t i o n networks, procedural semantics, selectional r e s t r i c t i o n s and semantic association, General IMPROVING METHODOLOGY I N NATURAL LANGUAGE PROCESS I NG W i l l i a m C. Mann USC Information Sciences I n s t i t u t e Marina D e l Rey, California", "pdf_parse": { "paper_id": "J75-2012", "_pdf_hash": "", "abstract": [ { "text": "Acquaints speech researchers i n the s t a t e of the a r t i n the conceptual development o f , and the new perspectives they place on, parsing, syntax and semantic i n t e r p r e t a t i o n. Includes the Chomsky hierarchy of grammar models, n0.n-determinism i n parsing and i t s implemen&ation i n e i t h e r backtrdcking or multiple in4ependent a l t e r n a t i v e s , predictive vs. non-predictive parsing, word l a t t i c e s and chart parsing, Early's algorithm, t r a n s i t i o n network grammars, transfornational grammars and augmented t r a n s i t i o n networks, procedural semantics, selectional r e s t r i c t i o n s and semantic association, General IMPROVING METHODOLOGY I N NATURAL LANGUAGE PROCESS I NG W i l l i a m C. Mann USC Information Sciences I n s t i t u t e Marina D e l Rey, California", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Abstract", "sec_num": null } ], "body_text": [ { "text": "methodology should be r e l i a b l e , e f f i c i e n t and have integrative power. The d i s t i n c t i v e strengths of the currenl computer oriented methodology are (a) t h e complexity of ,data and tzheory i s easy t o accommodate, (b) t i m e sequence and dependencies are preserved, and (c) a diversity of hypotheses can be t e s t e d . Weaknesses are (a) experbents often take years t o perform, (b) t h e a c t i v i t y i s treated as a programming exercise with the s t a t u s of data and program unc l e a r l y defined and (c) i n attempting to be general on a particular phenomenon, s i g n i f i c a n t others are missed. There are two tasks for which methodologies are used, (a) building intelligent: machines, and (b) under standing human language performance, Both depend on the development of a 'device-independent ' language, understanding theory. Fof theoretical studies, a methodology should be cognitively efficient and should deal effectively with the problem of scale--having a large number of facts embodied in the theory. Studies should be performed in the context of total language understanding; isolation of qomponents limits scope. Intuition on human language performance is a good guide to computational linguistics.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "Phonetics -.Phonology : .Recognition Contains 142 abstracts covering recognition, synthesis, and the acoustical, phonological and linguistic processes necessary in conversion of various waveforms. Retrieved using the National Tech~iical Information Service on-line search system. [570] [571] [572] [573] [574] [575] 1974 considers characters as a directed a b s t r a c t graph, of which the node set c o n s i s t s of t i p s , corners, and junctions, and t h e branch s e t ~o n s i s t s of l i n e segments connecting p a i r s of adjacent nodes. Classificat-ion of branch fypes produces features which a r e t r e a t e d as fuzzy variables. A character i s represented by a fuzzly function which r e l a t e s its fuzzy variables, and by the node p a i r involved i n each fuzzy variable. After producing a representation of an unknown character recognition occurs when a previously learned character's representation is isomorphic t o the unknown. A 16:l compaction r a t i o was achieved by s t o r i n g only the f i r s t instance of each p a t t e r n c l a s s and t h e r e a f t e r s u b s t i t u t i n g this exemp l a r for every subsequent occurrence of t h e symbol. Proposed a r e refinements t o y i e l d a 40:l r a t i o . Computers and the Humanities 9, 1: [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] 1975 Various proposals are discussed, principally (1) Rankin, who has a two-level grammar, the f i r s t gives the strokes and rules f o r combination and the second explicates the order, with a recursive d e f i n i t i o n of subframes . (2) Fuj imara has an inventory of strokes and operators. For each stroke 3 functional points are isolated and operators define the linking by reference t o these points. Applications include keyboard input, storage and r e t r i e v a l o r characters, and automatic recognition. There are two d i f f e r e n t approaches. One seeks a l o g i c a l l y e f f i c i e n t system; the other one t h a t seems n a t u r a l to a user of the language. An approach t o recognition of a block picture by comparing it with stochastic sectionalgrams obtained by grouping many samples. TO calculate the risk, t h e absolute values of t h e d i f f e r e n c e s between t h e stroke-occurrence p r o b a b i l i t i e s of corresponding quanta i n the two sectionalgrams a r e summed one of these two sectionalgrams being derived from the i n p u t p a t t e r n and t h e o t h e r from t h e prototype pattern. The smaller the sum of these d i f f e r e n c e s i s , t h e more accurate the input pattern tecognition. Hand printed on a standardizing grid made of twenty line segments, yielding twenty features, and input using a television camera, 49 character classes were recognized at a greater than 99.4% rate.", "cite_spans": [ { "start": 280, "end": 285, "text": "[570]", "ref_id": null }, { "start": 286, "end": 291, "text": "[571]", "ref_id": null }, { "start": 292, "end": 297, "text": "[572]", "ref_id": null }, { "start": 298, "end": 303, "text": "[573]", "ref_id": null }, { "start": 304, "end": 309, "text": "[574]", "ref_id": null }, { "start": 310, "end": 315, "text": "[575]", "ref_id": null }, { "start": 316, "end": 320, "text": "1974", "ref_id": null }, { "start": 1283, "end": 1287, "text": "[13]", "ref_id": null }, { "start": 1288, "end": 1292, "text": "[14]", "ref_id": null }, { "start": 1293, "end": 1297, "text": "[15]", "ref_id": null }, { "start": 1298, "end": 1302, "text": "[16]", "ref_id": null }, { "start": 1303, "end": 1307, "text": "[17]", "ref_id": null }, { "start": 1308, "end": 1312, "text": "[18]", "ref_id": null }, { "start": 1313, "end": 1317, "text": "[19]", "ref_id": null }, { "start": 1318, "end": 1322, "text": "[20]", "ref_id": null }, { "start": 1323, "end": 1327, "text": "[21]", "ref_id": null }, { "start": 1328, "end": 1332, "text": "[22]", "ref_id": null }, { "start": 1333, "end": 1337, "text": "[23]", "ref_id": null }, { "start": 1338, "end": 1342, "text": "[24]", "ref_id": null }, { "start": 1343, "end": 1347, "text": "1975", "ref_id": null } ], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "Feature values calculated utilizing a Gaussian point-to-line distance concept were used in a weighted minimum distance classifier. All character-dependent data are obtained through training techniques Both statistical linear regression and averaging methods are used to obtain the parameters defining each character class in feature space. Augmented phrase structure grammars consist of phrase structure rules with embedded conditions and structure building actions Data structures are records consisting of attribute-value pairs. Records can be actions, words, verb phrases, etc. There are three kinds of attributes: relations, whose value is a pointer to other records; properties, with values either numbers or character strings; and indicators, whose values have a role similar to linguistic featires. Structure building rules have a left part indicating the contiguous segments that must be present for a structure building operation, given in a right part, t o apply.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "SPEECH RECOGNITION BY COMPUTER : A BIBLIOGRAPHY WITH ABSTRACTS", "sec_num": null }, { "text": "Gramar : Parser.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Lexicoqraphy -", "sec_num": null }, { "text": "In R. Schank and B . L . Nash-Webber, eds., Theoretical Issues in Natural Language Processing, 1975, 6-14. The hypothesis is that every language user knows as part of his recognitAon grammar, a set of highly specific diagnostics that he uses to decide deterministically what structure to build next at each point in the process of parsin a sentepce. This theory rek jects 'backup as a standard contro mechamsm for parsing. A grammar is a set of modules. The parser works on two levels, a group level and a clause level. Group level modules work on a word buffer and build group level structures. Modules have a pattern, a pretest procedure and a body to be executed if the pattern matches and the pretest succeeds. If the parser fails, it keeps the structure constructed to date, and makes whatever substructures it can from the remaining part. a theme i s a g e n e r a l i z e d p a t t e r n t h a t i s a s s o c i a t e d w i t h a s i n g l e word, e . g . , ' 27, 1975 Discusses some of the problems that arise when the concept of a linguistic vatiable is combined with the concept of a fuzzy set: the range of the numerical base variable, in ordering usagR, is not fixed for a given linguistic variable. This file contains formal descriptions of word meanings, including q~alificatfons, informal explanations, and criticisms of descriptions. The wards used are found in the lexicons of the Speech Understanding Research groups being sponsored by ARPA. The semantic analysis produces 23 data fields for each word, of which the following are searchable: word, domain analysis number, source part of speech and components Other fields can be searched using a string matchin facility. This file is available via on-line f queries or in a isting format.", "cite_spans": [ { "start": 3, "end": 106, "text": "R. Schank and B . L . Nash-Webber, eds., Theoretical Issues in Natural Language Processing, 1975, 6-14.", "ref_id": null }, { "start": 967, "end": 970, "text": "27,", "ref_id": null }, { "start": 971, "end": 975, "text": "1975", "ref_id": null } ], "ref_spans": [], "eq_spans": [], "section": "Mitchell Marcus Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge", "sec_num": null }, { "text": "Semantics -Qiscourse. If semantic primitives are seen as essentially djtfferent from words, this leads to attempts to justify them directly, usually psychological~y. Otherwise the justification is merely that they work. Primitives can be taken as a small natural language, with no essential difference betQeen primitives and m r d e . But the set of primitives cannot be extended indefinitely. ptherwise the distinction between the representation end the nntural language will be lost. If it is not possible to escape f r w natural language into another realm, one cannot separate semantic representation from reasoning as is attempted. It is probably more sensible to say that natural. language understanding depends on reasoning rather than vice-versa. A key feature of the system is that the semantic deep structure of the non-verbal, behavioral, rules may be represented in the same network as the semantics for natural language grammars, and, as a consequence, provide non-verbal context for linguistic rules. The total system has the power of at least the 2nd Order predicate calculus. An analysis of the verb 'hand' is paraphrased as: 'S had Y prior to some t h e t at which X used his band to do something that caused Y to travel to 2, after which Z had Y' The analysis includes a dYscussion of the subsumed Concepts HAPPEN, USE, ACT, CAUSE, ALMW, BEFORE, TRAVEL, and AT. Comprehension is a memory process; breaking computational under standing into sccbyrob-leem af parsirig and semantic iktetpretation has hindered progress with much effort wasted on the construction of parsers. A system is described in which a monitor takes words from a sentence one at a time, from left to right. Reasoning may be propositional ar by mental simulation wing visual imagery. In the latter situation, do people include acts and objects not present in a given story, but necessary to carry out the simulation. This has not yet been experimentally tested.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Mitchell Marcus Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge", "sec_num": null }, { "text": "Experiments have shown that a listener may simulate a story from the point of view of an observer or of a participaht in the story. One problem that this raises for AI, if a program can construct an interconnected structure from the text, is the non-uniqueness of Listeners draw inferences from what they hear, but different listeners can make different inferences. One kind of inference in comprehension is in the context of given-new information: the speaker tries to construct the given and new information of each utterance, so that the listener is able to compute unique antecedents for the given information, and so that he will not already have the new information attached to the antecedent. Inference mechanisms include direct reference, identity, pronominalization, epithets, set membership, indirect reference by association, indirect reference by characterization, reaaons, causes, conseqQences, and concurrences. Bridging inferences need not be determinate, but in discourse they seemingly are, and further, are the inferences with fewest assumptions. Both backward and forward inferences are possible, but only the former are determinate. Generation is a two stage process. The first formulates a lan and the second expresses these intentions; there is feedback getween the stages. Intentions can be encoded by (i) establishing presuppositions, (ii) by linguistic conventions, and (iii) by discourse structure. kSoc*al Actioii Paradigm is a model of the flow of social actions. In generating natural language from a conceptual structure words and syntactic structure must be deduced from the information content of the message. Words are accounted for by a pattern matching mechanism, a discrimination net. The case framework of verbs is one source of knowledge for choice of syntactic structure. Technological computational linguistics is primarily concerned with software technology whereby computers can use and process natural language. Descriptive computational linguistics uses the computer a6 a means of developing an accurate and empirically valid model of linguistic and cognitive behaviors of human speakers. There is no inherent representation of intentions in the former, and experience is that it cannot easlly be generalized to.the latter. One problem of modeling is that important things are often hidden by their familiarity. Both propositional and non-propositional knowledge must exist. Interpretive processes during perception individuate and categorize objects. If an object cannot: be categorized then the object will be stored with analogic information. During verbalization analogic images will be compared with available category prototypes to decide on the best match for use in the utterance. ", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Semantics -", "sec_num": null }, { "text": "Semantics -Discourse : Memory R E P R E S E i I T A T I O N AND U f j D E R S T A l i D 1 ! ' d G STUDIES I N C O G N I T I V E S C I E N C E", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Semantics -", "sec_num": null }, { "text": "M i l l e r . . . . . . . . . . . . . . . . . . . . . . . 383", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Reasoning from incomplete knowledge A l l a n C o : l i n s , E l e a n o r H . Warnack, N e l l e k e A i e l l o , and Mark L .", "sec_num": "13." }, { "text": "The preface is reprinted an the following frames by permission.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Reasoning from incomplete knowledge A l l a n C o : l i n s , E l e a n o r H . Warnack, N e l l e k e A i e l l o , and Mark L .", "sec_num": "13." }, { "text": "P r e f a c e J a i m e Carbonell was our friend and colleague. For many years he worked with 11s on problems i n Artificial Intelligence, especially on t h e developrnerit of RII intelligent instructionnl system. Jainle directed t h e Artificinl Intelligence group e t Bolt, Deranek, and Ncwman (in Cambridge, Massnchusetts) until h i s death i n 1973. Some of us who hod worlred with Jaime decided to hold a conference i n his nlemory, a confcrerlce whose guiding principle wonld be t h a t Jaime would have enjoyed it. T h i s book is the result of t h a t conferencb.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "REPRESENTATION AND UNDERSTANDING", "sec_num": null }, { "text": "J a i n~e Carbonell's isnportant contribution to cognitive science is best sumnlarized in t h e title of one of his publicatio~ls: A7 irt CAI. Jaime wanted t o p u t principles oE Aritificial Intelligence i n t o Computer-Assisted Instruction (CAI) systems. H e dreamed of a system which had a data base of knowledge about a topic matter and general information about language and t h e principles of tutorial instruction.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "REPRESENTATION AND UNDERSTANDING", "sec_num": null }, { "text": "The system could then pursue a natural tutorial dialog with a student; sometimes following the student's initiative, sometimes taking i t s own intiative, but always generating i t s statements rind responses i n a natural way from its general knowledge. T h i s system contrasts sharply with existing systems for Computer-Assisted Instruction i n which a relatively fixed sequence of questions and possible reponses have to be determined f o r each topic. J a i m e did construct working versions of h i s &ream--in a system which he called SCHOLAR. B u t h e died befoi-e SCHOLAR reached t h e full realization of t h e dream.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "REPRESENTATION AND UNDERSTANDING", "sec_num": null }, { "text": "It was a pleasure to work with Jaime. His kindness and h i s enthusiasm were infectious, and t h e discussions we had with him over the years were a great stimulus t o o u r own thinking. Both as a friend and a colleague we miss him greatly.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "REPRESENTATION AND UNDERSTANDING", "sec_num": null }, { "text": "Cognitive Science. T h i s book contains studies in a new field we call cognitive science. Cognitive science includes elements of psychology, computer science, linguistics, philosophy, and education, b u t i t i s more than t h e intersection of these disciplines. Their integration has produced a new set of tools for dealing w i t h a broad range of questions. In recent years, the interdctions among the workers in these fields has led to exciting new developments in our undemtanding of intelligent systems and the development of a science of cognition. The group of workers has pursued problem$ that did not appear to be solvable from within any single discipline. It is too early to predict the future course of this new interaction, but the work to date has been stimulating and inspiring. I t i s our hope that this book can serve as an illustrntion of the type of problems Chat can be qq~roached through interdisciplinary cooperation. The participants in this book (and at the conference) represent the fields sf Artificial Intelligence, Linguistics, and Psychology, all of whom work on similar problems but with different viewpoints. The book focuses on the common problems, hopefully acting as a way of bringing these issues to the attention of all workers in those fields related to cognitive science.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "REPRESENTATION AND UNDERSTANDING", "sec_num": null }, { "text": "Subject Matter. The book contains four sections. In the first section, Theory of Representotion, general issues involved in building representations of knowledge are explored. Daniiel G. Bobrow proposes that solutions to a set of design issues be used as dimensions for comparing different represetltations, and he examines different forms such solutions might take. William A. Woods explores problems in representing natural-language statements i n semantic networks, illustrating difficult theoretical issues by examples. Joseph D. Becker is concerned with the representation one can infer for behavioral systems whose internal workings cap not be observed directly, and he considers the interconnection of useful concepts such as hierarchical organization, system gaals, and resource conflicts Robert J. Bobrow and John Seely Brown present a model for an expert understander which can take a collection of data &scribing some situation, synthesize a contingent knoultedge structure which places the input drrta in the context of a larger structural organization, and which answers questions about the situation based only on the contingent knowledge structure.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "REPRESENTATION AND UNDERSTANDING", "sec_num": null }, { "text": "Section two, New Memory Models, discusses the implications of the assumption that input information is always interpreted i n terms of large structural units derived REPFLESENTATION AND UNDERSTANDING from esporionce. Daniel G. Bobrow and Donnld A. Norman postulate active sciicrnnla i n memory which r~f e r to each other through use of car~tuxl-deper~derlt descriptions, and whir11 respo~irl both to input data and to hypothcs~s about structure. Benjamin J. Kuipers describes thc conc~l)t of a frame us a structural organizing unit for data ele~nents, nnd he discusses the use of these units in the context of n recognition system. Terry Winogrod explores issues i~lvolved in the controversy on rcl~rcsc~lting knowledge i u declarative vcrsus procedural form.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "REPRESENTATION AND UNDERSTANDING", "sec_num": null }, { "text": "Winogr~tl uses the concept of a frame ns a basis for the synthesis of the declarative and proccdural tipproaches. The frame provides an organizing structure on which to attach both declarative and procedural informhtion.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "REPRESENTATION AND UNDERSTANDING", "sec_num": null }, { "text": "T h e third section, l l i g h e r Level S t r u c t u r e s , focuses on the representation of plans, episodes, and stories within memory. David E. Rumelhart proposes a grammar for wellformed stories. 'His summarization rules for stories based on t h i s grammar seem to provide reasonable predictions of human behavior.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "REPRESENTATION AND UNDERSTANDING", "sec_num": null }, { "text": "Roger C. Schank postulates that i n understanding paragraphs, the reader fills in causal connections between propositions, and t h a t such causally linked chains are t h e basis for most human memory organization. Robert P Abelson defines a notation in which to describe the intended effects of plans, and to express the conditions necessary for achieving desired states. T h e fourth section, Semantic Knowledge i n U n d e r s t a n d e r Systems, describes how knowledge has been used in existing systems. John Seely.Brown and Richard R. Mark L. Viller describe a continuation of work on Jaime Carbonell's SCHOLAR system. They examine how liumans use strategies to find reasonable answers to questions for which they do net have the knowledge to answer with certainty, and how people can be taught t o reason this way.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "REPRESENTATION AND UNDERSTANDING", "sec_num": null }, { "text": "Acknowledgments. We a r e grateful for t h e h e l p of o largo number of people who made the conference and this book possible. The conference partici.pants, not all of whom are represented i n this book, created an atmosphere i n which interdisciplinary exploration became a joy.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "iii REPRESENTATION AND UNDERSTANDING", "sec_num": null }, { "text": "The people attending were:", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "iii REPRESENTATION AND UNDERSTANDING", "sec_num": null }, { "text": "From Julie Lustig made all the arrangements for t h e conference a t Pajaro Dunes, and was largely responsible for making i t a comfortable atmosphere i n which to discuss some very difficult tecllnical issues. Carol Van Jepmond was responsible for typing, editing, and formatting t h e manuscripts to meet the specifications of the pysterns used i n the production of this book. It is thanks to h e r skill and effort t h a t t h e book looks as beautiful as i t does. J u n e Stein did t h e final copy editing, made general corrections, and gave many valuable suggestions on format and layout.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "iii REPRESENTATION AND UNDERSTANDING", "sec_num": null }, { "text": "Photo-ready copy was produced with t h e aid of experimentd formatting, illustration, and printing systems built a t the Xerox Palo Alto Research Center. We would like to thank Matt Heile-r, Ron Kaplan, Ben Kuipers, William Newman, Ron Rider, Bob Sproull, and Larry Tesler for their help in making photo-ready production of this book possible. We are grateful t o the Computer Science Laboratory of t h e Xerox Palo Alto Research Center for making available t h e experimental facilities and for i t s continuing support. Frames are static structures about one stereotyped topic", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "iii REPRESENTATION AND UNDERSTANDING", "sec_num": null }, { "text": "Each frame has many statements about the topic, each expressed in a suitable semantic representation. The primary goal in understanding is to find instances of frame statements in the discourse Questions about a source statement can be answered by reference to the frame of which it is en instance.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "iii REPRESENTATION AND UNDERSTANDING", "sec_num": null }, { "text": "Semantics -Discourse : Memory", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "iii REPRESENTATION AND UNDERSTANDING", "sec_num": null }, { "text": "By systematic application of a cognitive network or similar theory of knowledge the internal structure of a (medical) code can be improved and tools developed for different purposes. Hays's theory uses paradigmatic, syntagmatic, discursive, attitudinal, and metalingual (MTL) arcs. The MTL arcs shift level of abstraction; e.g., anemia is neither a fewness nor an erythrocyte but an abstract condition. An abstract definition can include several syntagmatic propositions, linked discursively. A medical term can be linked by ", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Journal o f C l i n i c a l Computing, 3 , 110-118, 1973", "sec_num": null }, { "text": "' K ferent kinds of knowledge. The dbtinction as been rejected, because it i s said that since we know everything Erom experience, there is no room for the distinction. The error lies in confusing knowledge from knowledge, and knowledge of knowledge. Semantic knowledge is knowledge that has been reorganized around concepts from knowledge originally encoded around events; it fs stripped of personal experience. One question raised by the distinction is how does information get into semantic memory, and how and when does it get 10s t from episodic memory. There is evidence that people use three-dimensional models and that they integrate several views into a single model. This is counter to the claim that we symbolically store a large number of separate views. Another problem is with the assumption of default values for slots in frames. In the extreme, this gives visual perception without vision. The evidence is that people can understand totally unexpected images presented for quite short pexiods. A rhird point concerns the telatively static nature of frames. A better model is to condtruct a goal oriented subsystem making use of context specific knowledge. Using for illustration a recognition system for chromosome structures, methods are developed which basically consist of applying error transformations to the productions of context-free grammars in order to generate new context-free grammars capable of describing not only the original error free patterns, but also patterns containing specific types of errors such as deleted, added, and interchanged syinbofs which often arise in the pattern-scanning process. Artificial Intelligence has had at least four benefits for the study of natural language: (a) emphasis on complex stored structures, (b) emphasis pn the importance of real world knowledge, (c) em hasis on the communicative function of sentences in context, and (dy emphasis on the expression of rules, structure and information within the operational environment. The only test of a natural language system is its success on a task, any demand for more theory must bear this in mind. Neither can recent work in A 1 be regarded as theoretical; it is the semi-formal expression of intuition. A1 is engineering, not a science, and as such there is no boundary to natural language; one counter example does not overthrow a rule system. Further, talk of theory distracts from heuristics. A model of reasoning about human action must include (1) how people arrive at a plan, (2) what can count as a reason for choosing to perform the plan, and (3) discovering plans and motivations from observation or linguistic report of actions. A plan is the internal representation or set of beliefs about how a particular goal may be achieved. The belief by an observer that an actor performed one act to enable a second to be performed can follow neither from deductive nor inductive reasoning. An observer may have other propositions that are reasons for believing or nut believing that a plan correctly characterizes the beliefs of the actor. An act name organizes a set of beliefs about how a move of this type might relate to other moves, and the cognitive and motivational statea of the actors.", "cite_spans": [ { "start": 2503, "end": 2506, "text": "(2)", "ref_id": null } ], "ref_spans": [], "eq_spans": [], "section": "The distinction between semantic and episodic memory is not so much one between different kinds of memo , but one between dif-", "sec_num": null }, { "text": "Discourse", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Semantics -", "sec_num": null }, { "text": "Ralph E. Griswold P r e n t i c e -H a l l , Inc. Englewood C l i f f s N e w Jersey ", "cite_spans": [], "ref_spans": [ { "start": 9, "end": 51, "text": "Griswold P r e n t i c e -H a l l , Inc.", "ref_id": null } ], "eq_spans": [], "section": "STRING AND LIST PROCESS I NG IN SNOBOL4: TECHNIQUES AND APPLICATIONS", "sec_num": null }, { "text": "A. Colin Day his boo^ ranges over topics from plotting on a line printer to hashing and basic storage structures (stacks, queues, etc.) using a concise, to-the-point writing style. This style reinforces the stated intention of the book, which is to heLp a programmer with a problem by providing descriptions of non-mathematical techniques. The style and intention do limit the usefulness of this book, as some of the topics would be well known to advanced programmers and are not covered in sufficient depth for such a person. It is then the area between these two extr'emes to which this book is aimed, and there it can be of great service.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "F O R T R A N T E C H N I Q U E S WITH SPECIAL REFERENCE TO NON-NUMERI CAL APPLICATIONS", "sec_num": null }, { "text": "The only important assumption made of the reader is that be know the variable types of Fortran (integer, real, Hollerith, etc.) and their attendant foymat specifications. A good knowledge of character formats is especially useful, although the major use for them is in output statements used in the examples given in the book. It is also assumed that the reader knows the basic Fortran statements, but this is simple matter as opposed to the format and variable type problems which confront a Fortran programmer.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "F O R T R A N T E C H N I Q U E S WITH SPECIAL REFERENCE TO NON-NUMERI CAL APPLICATIONS", "sec_num": null }, { "text": "The bodk also includes several exercises at the end of each chapter (answers not supplied unfortunately) and a short but very complete bibliography which includes several sources for each chapter.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "F O R T R A N T E C H N I Q U E S WITH SPECIAL REFERENCE TO NON-NUMERI CAL APPLICATIONS", "sec_num": null }, { "text": "The book's primary value is as a source for Hints to problems encountered during programming, providing an introduction to the'more sophisticated literature which can be found by starting with the bibliography. This book is therefore a starting point for picking up a basic vocabulary, techniques, and references for someone who has just completed a programming course or who needs a quick introduction to some technique which he may want to look at later in more detail.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "F O R T R A N T E C H N I Q U E S WITH SPECIAL REFERENCE TO NON-NUMERI CAL APPLICATIONS", "sec_num": null }, { "text": "Computation : Information Structures I N F O R M A T I O N S Y S T E M S VOLUME 1 NUMBER 2 APRI L 1975", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "F O R T R A N T E C H N I Q U E S WITH SPECIAL REFERENCE TO NON-NUMERI CAL APPLICATIONS", "sec_num": null }, { "text": "Hans-JochenSchneider, Editor-ln-Chief Sensory data is considered as having several levels of interpretation. At the sensory end, the representation is analog, and propositional at the cognitive end. Analog images are incorrectly seen as having all details of the stimulus whereas quasi-linguistic representations are only partial. The important issue is not the partiality but the selection, possibly information that discriminates the object&n_c~texJ, Fokstru_c_ral information there needs to be a mechanism for both parts ana wholes. Parametric information can be coded componentially and explicitly, but some seems to function integrally. It is claimed that structural perception is qualitative whereas parametric perception is quantitative, but structural elements may have quantitative aspects--its strength of association with different groups. Although both structure and parameters are encoded relative to other information, thexe is evidence of preferred orientation and perspectives for parameters Processing, 1975, 164-168. The distinction between Fregean (symbolic) and analogical representations is that in the latter both representation and thing must be complex and there must be correspondence between the structures, whereas in the farmer case there is no need for a correspondence. Attempts to subsume either representation under the other have not succeeded. There is a mistaken belief that only proofs in Fregean symbolism are rigorous. Although analogical representations can sometimes be implemented using Fregean ones, this does not imply that they are not used. Lemmatized and classifying index, verse concordance, rhyming index, reverse morphological index frequency list, computer-readable \"MHG Working Dictionary\" \"Syntactical Rule System' making possible a mechanical text description and expandable to a \"descriptive grammar\". The processing of discourse is generally organized around verbs. However the structure at a topical or thematic level may not be so organized, bearing little resemblance to a deep structure. Analogies are used, not only in poetry, to transfer large amounts of information from one domain to another; to enable communications of the otherwise. inexplicable; to make distinctions vivid; and to understand new concepts by analogy to old ones.", "cite_spans": [ { "start": 1008, "end": 1034, "text": "Processing, 1975, 164-168.", "ref_id": null } ], "ref_spans": [], "eq_spans": [], "section": "F O R T R A N T E C H N I Q U E S WITH SPECIAL REFERENCE TO NON-NUMERI CAL APPLICATIONS", "sec_num": null } ], "back_matter": [ { "text": " Processing, 1975, 180-195. Commonsense algorithms are basic structures for modeling human cognition. The structure is defined by specifying a set of links which build up large structures of nodes of five types: Wants, Actions, States, Statechanges and Tendencies. There are 25 primitive links, e.g., one-shot causality, action concurrency, inducement Various applications are active problem solving, basis for conceptual representation of language, basis of self model, etc.", "cite_spans": [ { "start": 1, "end": 27, "text": "Processing, 1975, 180-195.", "ref_id": null } ], "ref_spans": [], "eq_spans": [], "section": "annex", "sec_num": null }, { "text": "Charles F. Schmidt Processing, 1975, 196-200. [177] [178] [179] [180] [181] [182] [183] [184] 1973 The Medical Advances Institute developed a system to keep records, select cases for review, and information about individuals and categories, for the quality control system now established by law. Over 200 quality criteria packages have been developed. They concern the process and result of medical care. The system screens each case within a day of hospital admission and frequently thereafter. It provides a review of use of facilities and conformity to standards of care. Documentation : Retrieval", "cite_spans": [ { "start": 19, "end": 45, "text": "Processing, 1975, 196-200.", "ref_id": null }, { "start": 46, "end": 51, "text": "[177]", "ref_id": null }, { "start": 52, "end": 57, "text": "[178]", "ref_id": null }, { "start": 58, "end": 63, "text": "[179]", "ref_id": null }, { "start": 64, "end": 69, "text": "[180]", "ref_id": null }, { "start": 70, "end": 75, "text": "[181]", "ref_id": null }, { "start": 76, "end": 81, "text": "[182]", "ref_id": null }, { "start": 82, "end": 87, "text": "[183]", "ref_id": null }, { "start": 88, "end": 93, "text": "[184]", "ref_id": null }, { "start": 94, "end": 98, "text": "1973", "ref_id": null } ], "ref_spans": [], "eq_spans": [], "section": "Computation : Inference", "sec_num": null }, { "text": "A", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "PSRO -", "sec_num": null }, { "text": "In; Information Storage and Retrieval, Gerard Salton, Editor. R e p r t No.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Cornell University Ithaca, New York", "sec_num": null }, { "text": "Experimental results indfcate that final retrieval system performance, after user feedback is applied using Rocchio's algorithm, is highly dependent on the system performance of the initial indexing process. Thkrefore every tool which imgroves thc indexing performance as an outcome of the content analysis of natural language is beneficial because initial differences in a system performance are retained after user feedback is applied. SNOP, published in 1965, is not rich enough to code problems, signs, symptoms, disease entities, administrative, diagnostic, and therapeutic procedures. SNOMed is to cover the whole. The code is hierarchical: Topography is organized by system or tract, Morphology by such categories as traumatic, neoplasm, etc., Etiology by categories of organisms and chemicals, Normal function by metabolism, enzyme, etc., Abnormal function correspondingly, and Procedure by medical discipline. Qualifiers such as history of, laboratory diagnosis, etc., are included, and terms aan be linked. Clinical Computihg, 3, 164-171, 1973 To improve the management o f Medicaid, which spends (predicted) $9 billion for 27 million persons in 1974, an information system was designed and installed in a pilot state. It maintains data about eligibility of persons, qualification (administrative) of providers, claims, background (e.g. normal prices); it delivers statistical dummaries and exception reports for managers in addition to processing claims. Sentences describing scenes centred around a clown who can balance and move are analyzed by an ATN parser. The parser produces prop6rty list semantic structures which are adequate to transmit data to a package that generates the scene on a display screen. Humanities, 8 : 93-98, 1974 Discusses the development of this form of content analysis in information retrieval, the social sciences, and literary analysis. Gallarate, Italy has begun to publish the long awaited massive concordance to his writings and to texts by other authors long associated with his circle. For many of us who have done lesser work in computerized humanistic studies, rumors and reports of Busa's enterprise aroused our curiosity and, in some cases, led us also to grapple with the manifold problems of producing a concordance by computer.", "cite_spans": [ { "start": 1017, "end": 1053, "text": "Clinical Computihg, 3, 164-171, 1973", "ref_id": null }, { "start": 1722, "end": 1749, "text": "Humanities, 8 : 93-98, 1974", "ref_id": null } ], "ref_spans": [], "eq_spans": [], "section": "ISR-22, November 1974", "sec_num": null }, { "text": "In studying the specifications and sampling the first ten volumes of Index Thomisticus (Seatio 11, Concordantia Prima (A-Initor)) , this reviewer has been reminded of his own struggle to produce a concordance to the Institutes of ~o h n Calvin (Pittsburgh, 1972) . The r . T. provides a hierarchically organized concordance to a literary corpus of 10,600,000 words of Latin Texts; by comparison, the CaLvin concordance contains 405,338 words of Latin text in a single sequence.Thus, the vastly greater literary task of Busa called for a series of basic literary and philological and logical declsions not only to make the enormous work of processing possible, but also to produce a final instrument for the use of scholars that would rationally encompass the vaat corpus.At the outset the character of the Latin language and especially its morphological peculiarities had to be translated into computerizable routines, so that something other than a sea of raw a lphabetical sdrting would result. Lematization by hand sorting after the basic concordancing (feasible for a small corpus), preparation of an interlined (\"glossed\") lemmatized machine readable rext (also suitable for smaller texts), even the elaborated encoding of the text developed by De Latte at the Liege Centrenone of these methods was chosen by Busa and his associates. They turned rather to Forcellini ' s Lexicon tot ius ~a t i n l h t i s and encarded the 90,000 Forcellini lemmata (in all possible forms) plus additional ones in the Thornistic corpus to a total of 10,000,000 codes, put this on magnetic tape, and worked out procedures to apply this Latin Machine Dictionary (LEL) to the machine-readable text. This instrument is now available fox the use of others working on Latin texts. To anyone knowing the homographs of Latin, the limitations of any mechanical routine are apparent: the T., however, handles these problems in a clear and workable manner. A massive concordance of this type must carry a concise yet:precise location code for each item. The editors have determined the proper modern edition to be used, have set a precise order of works to be followed In the concordancing of each type under its appropriate lemma, and have summarized this on a separate 4-page insert, to whidh the user will doubtless make frequent reference as he learns to use this grand instrument of research.A short review cannot do justice to the immense detail and the intelligence with which this detail has, with human and computer help, been marshalled in the I . T . Ea'ther Busa and his associates are to be commended not only for their achievement, but: also for the example they have set for other laborers. ", "cite_spans": [], "ref_spans": [ { "start": 244, "end": 262, "text": "(Pittsburgh, 1972)", "ref_id": null } ], "eq_spans": [], "section": "Minneapolis", "sec_num": null } ], "bib_entries": {}, "ref_entries": { "FIGREF0": { "type_str": "figure", "num": null, "text": "As whole systems are produced, they a r e d i f f i c u l t t o disseminate and jud e. A systemmay process i t s examples, but i r i s hard t o determine i it is ad-hoc and tuned t o the examples.", "uris": null }, "FIGREF1": { "type_str": "figure", "num": null, "text": "Schank and B.L. Nash-Webbar eds. Theoreticel fssues in Natural LanguageProcessing, 1975, 134-139.", "uris": null }, "FIGREF2": { "type_str": "figure", "num": null, "text": "Systems, Man and Cybernetics, $Me-#!", "uris": null }, "FIGREF3": { "type_str": "figure", "num": null, "text": "Writing : Recognition A MEANS OF ACHIEVING A HIGH DEGREE OF COMPACTlON ON SCANDIGITIZED PRINTED TEXT R. N. Ascher and G. Nagy IBM Corporation IEEE Transactions on Computers, C-23) 1174-1179, 1974", "uris": null }, "FIGREF4": { "type_str": "figure", "num": null, "text": "Writing : Reco-gnitianA SURVEY OF MODELS AND APPLICATIONS W i l l i a m S t a l l i n 6 Center f o r Nava f Analyses Arlington, Virginia", "uris": null }, "FIGREF5": { "type_str": "figure", "num": null, "text": "i l l i p s Department of Information Engineering U n i v e r s i t y of I l l i n o i s a t Chicago C i r c l e Doctoral dissertation, S t a t e U n i v e r s i t y of New York, Buffalo, 1975 A t h e o r y f o r t h e s t r u c t u r e of d i s c o u r s e i s developed. I t i s sh~wn t h a t p r o p o s i~i o n s of a coherent d i s c o u r s e must be l o g i ca l l y cbnnected and e x h i b i t a h i e r a r c h i c thematic s t r u c t u r e t h a t has a s i n g l e r o o t . An eqample of a l o g i c a l connective i s ' C a u s e ' ;", "uris": null }, "FIGREF6": { "type_str": "figure", "num": null, "text": "' i s d e s c r i b a b l e a s 'Someone i n g e s t s something that causes him t o become i l l ' . A theme a p p l i e s t o a d i s c o u r s e i f 2 t s d e f i n i e n s matches p a r t of t h e d i s c o u r s e . The t o p i c of a coherent d i s c o u r s e i s i t s m a t r i x theme; an i l l f o r m e d d i s c o u r s e has no t o p i c . Not a l l d i s c o u r s e s t r u c t u r e i s expressed. If omitted, i t m u s t b e i n f e r r a b l e . The process of i n f e r e n c e r e q u i r e s a store of world knowledgeencyclopedic knowledge. An encyclopedia i s desc r i b e d t h a t c o n t a i n s a l l t h e devices reqursed by t h e d i s c o u r s e a n a l y s i s problem. I n f a c t , t h e encyclopedia i s s g e n e r a l model f o r human c o g n i t i o n and i s a p p l i c a b l e t o inany d i v e r s e cognStive t a s k s . The encyclopedia i s a d i r e c t e d graph. C a t e g o r i e s of nodes agd a r c s , and of p r o c e s s e s , are p r e s e n t e d i n d e t a i l", "uris": null }, "FIGREF7": { "type_str": "figure", "num": null, "text": "Canonical reprebentations of cqnceptualisations are composed of an ACTOR, an ACTION and a set of ACTION dependent cases. The 12 primitive actions are ATRANS, transfer of possession; PTRANS, transfer of physical location; MTRANS, transfer of information; PROPEL, application of physical force; M13UILD construction of new conteptual information; INGEST, taking in of an object by an animal; GRASP, to grasp; ATTEND, to focus sense organ on an object; SPEAK, to make a noise; MOVE, to move a b.ody part; &WEL, to push something out of the body; and PLAN, which characterizes the ability to form a course of action that leads to a goal. Semantics -Discourse George A. Miller In R. Schank and B.L. Nash-Webber, eds., Theoretical Issues in Natural m g u a g e Processing, 1975, 30-33.", "uris": null }, "FIGREF8": { "type_str": "figure", "num": null, "text": "Schank and 8 . 1 ; . Nasb-Webber, eds. Theoretical Issues in Natural Language Processing, 1975, 24-29. Primitive functions GO, BE an8 STAY can be extended from a positional interpretation to possessional and identificational interprecations. Two kinds of m u s e are distinguished, CAUSATIVE and PERMISSIVE. Inference rules based on the form of semantic representations derive logical entailments. e.g. CAUSE, ( X , E ) --E . Semantics -Piscourse . Comprehension Christopher K. RIesbeck IA R. Schank: ,and. B;L; Nash-webber, eds., Theoretical Issues in Natural Language Processing, 1975, 11-16.", "uris": null }, "FIGREF9": { "type_str": "figure", "num": null, "text": "From a lexicon expectatisns. of the word (or its root) are added to a master list of expectations. If an element of the master list evaluates m true', programs associated with the element are executed. The final structure built by the triggered expectations is the meaning ~f the sentence. Semantics -Discourse : Comprehension Robert P. Abelson Yale University New Haven Connecticut In: R. Schank and B.L. Hash-Webber, Eds., Theoretical Issues in Natural LanguageProcessing, 1975, 140-143.", "uris": null }, "FIGREF10": { "type_str": "figure", "num": null, "text": "Dedicated to the memory of JAIME CARBONELL, 1928-1973 1. ~imensions of representation D a n i e l G . B o b r o w . . . 1 2. What's in a link: Foundations for semantic networks W i l l i a m A. W o o d s . . . . . . . . . . . . . . . . . . 3 53. Reflections on the formal description of behaviorJ o s e p h D . B e c k e r . . . . . . . . . . . . . . . . . . 8 3 4. Systematic understanding: Synthesis, Analysis, and contingent knowledge in s p e c i a l i z e d understanding systems Robert J. B a b r o w a n d J o h n ~e e l y B r o w n . . . 1 0 3 11 !~EW MEMORY MODELS 5. Some principles of memory schemata D a n i e l G. ~o b r o w a n d D o n a l d d . N o r m a n . . . . . . . . . . . . . . . . 1 3 i 6. A frame for frames: representing knowledge for", "uris": null }, "FIGREF11": { "type_str": "figure", "num": null, "text": "expertise in teachiog a student about debugging electronic circuits. Bonnie Nash-Webber describes the role played by semantics in the understanding of continuous speech in a limited domain of discourse.Allan Collins, Eleanor H. Warnock, Nelleke Aiello, and", "uris": null }, "FIGREF12": { "type_str": "figure", "num": null, "text": "scheme for creating structured concept nodes tn a semantic network is presented, with structuring techniques based op a set of primitive link types including: defined as attribute part, modality, role, structural/condition, valuelrestriction, subconcept and superconcept. This structure will atore descriptions of bibliographic references in a way that will facilitate the important processes of inference, paraphrase and analogy.Semantics -Discourse: Memory Allan Collins Bolt Beranek & Newman Cambridge, Mass. 02138 Iai R . Schnk and B.L. Nash-Webber, eds., Theoretical Issues i n Natural Language Processing, 1975, 52-54. Tulving's episodic memory is seen as a record of experiences and their context. However, both episodic and semantic memories must have similar power of representation, so their structures are not disttnguishable. Similarly, a lexical memory must have the power to represent propositional information about words. Thus, the fabric of knowledge is merely cut into different shapes. Schank and B.L. Nash-Webbet, eds., Theoretical Issues in Natural Language Processing, 1975, 79-83. A uniform formal structure for the interpretation of events, initiation of actions, understanding language, and using language The components of the system are CONTROL --the procedura is component; SCHEMATA --a lattice whose points are lexical decompoeitions; LEXICON --non-definitional infomation; BELIEFS -a closed and consistent set of statements in a predicate calculus; and GOALS. Semantics -Discourse : pemory Andrew Ortony University of Illinois at Urbana-Champaign In: R. Sclaank and B.L. dlash-Webber, Bds., Theoretical Issues in Natural LanguageProcessing, 1975, 55-60.", "uris": null }, "FIGREF13": { "type_str": "figure", "num": null, "text": ". Scharik and B.L. Bash-Webber, eds., Theoretical Issues i n Natural Language Processing, 1975, 89-91. Stories are broken down into schemata, e.g., plot plus moral. Questions about schemata are: what are the essential ingredients of a schema; are some more abstract thah others ; and how are they to be discovered--by imagination and intuition? STEREOTYPES AS AN ACTOR APPROACH TOWARDS SOLVING THE PROBLEM OF PROCEDURAL ATTACHMENT I N FRAME THEORIES Carl Hewitt In: R.SchalJt and B.L. Nash-Webber, eds., Theoretical Issues i n Natural Language &hank and B.L. Nash-Webber, ds., Theoretical Issues i n Natural Language Processing, 1975, J04-116. Frames are data 8 tructures for representing Stere~typed situations. Each frame contains information about how to use the frame, what to expect to happen next, and what to do if the expectations are not fulfilled. Lower levels of a frame have termfnals that can be filled by specific instances from source statements. Frames are linked together into a frame system and the action to go from one to another indicated. Different fraples can share the same terminals. Unfilled slots in instances of frames are filled by default optiorls from the general frame. of the naming behavior of the community is a suitable preliminary step in thesaurus building. It would determine what are terms to be entered, how they are related, and what theoretical differences require alternative definitions of the same term. kinguistics -Methods SYNTACTIC RECOGNITION OF INPERFECTLY SPEC I F 1 ED PATTERNS M. 6 . Thomason and R. C. Gonzalez Tennessee University IEEE Transactions on Computers, C-24: 93-95, 1975", "uris": null }, "FIGREF14": { "type_str": "figure", "num": null, "text": "ColumbiaIn: R.. Schank bnd B.L. Nash-Webber, Eds., Theoretical Issues i n Natural LanguageProcessing, 1975, 175-179. There are two mechanisms for formal reasoning: (a) resolution pxinciple, a campetence model, b virtue of its completeness, and (b) natural deductive systems, w g ich are attempts to define a perforrnance model for logical reasoning. A system could be designed that interfaces the two systems, each doing what it does best. Natural deductive systems have not considered fuzzy kinds of reasonfng. Future questions concern other quanrifiers, concexrs for representing wanting, needing, etc., and the balance between computation and deduction.", "uris": null }, "FIGREF15": { "type_str": "figure", "num": null, "text": "Reviewed by Norman Badler Department o f Computer and I n f o r m a t i a n Science The Moore School of E l e c t r i c a l Engineering University o f Pennsylvania Among popular computer p r o g r d g languages, SNOBOL4 stands out as the only one offering complex pattern definition and mtching capabilities. It also has a flexible function definition facility and programmer-defined data types. While not unique, these two features encourage problem-dependent extensions of the language. . All ? b e e aspects of SNOBOLA fom the basic tools in Griswold's new book Intended a s a text for the SNC1BON user (it i s not an \"introductoryt' text), it presents techniques for the representation and manipulation of data in string, list, o r otherwise \"structured\" fm. The text includes m y programed examples, problems with a wide range of difficulty, and answers t o m y of these problems. The first Shree chapters develop pattern matching, function definition, and data s-tructures. The l a s t four chapteFs examine particular application domiins: mthem t i c s , cryptography, document ~r p a r -~o r Plus a f e w more specialized problems. Although t h i s m y seem tb ignore c q u t a t i o n a l linguistics, the greatest imnediate benefit f o r the pmgranurter l i e s in the fFrst t h e chapters anyway. Within C h a p 1, the section on g r a m w s and patterns can be used f o r the inIplemntation of simple syntactic analysis. For exaqle, there i s a straightforward mpping of a BNf g~m m a r into SNOBON patterns, but there are p i t f a l l s (as well a s scsne more efficient representations in the balance) that the programer ought t o know. These are c'arefully explained. A topic that I f e l t was inadequately covered in Chapter 1 was the definition of the pattern mtching mechanism i t s e l f . The immediate presentation of examples using pattern rratchhg (page 2) calls for a brief overview of pattern m t c h h g syntax and seman-tics. Surely a progrwnnw? muld appreciate not having t o refer back t o his in.troductory text should some p a t t e n function or construct bebhazy i n his memory. Even an appendix wuld be satisfactory. In addition, t h i s would support the section on p t t e r n s a s procedures by providing the underlying semantics for such tlprocedures. EUrther incentive f o r i t s inclusion i s provided by. the excellent review of progt-annner-defined data types in Chapter 3. Why leave pattern mtching t o the userJ.s recollection? The function definition f a c i l i t y discussed in Chapter 2 eraables the constructic of generic functions. Since there are no data type declarations f o r function argunents or parwters, often only one function i s required for the execution of related op&ations.on various data types. The proliferation of functions in a complex system might therefore be systemtically reduced., The burdeg f a l l s on the progrmer, of course, to sort out +he admissible combinatians or appropriate actions. An addition function for real and cmplex numbers is discussed, where the f o m is a SNOBOL4 primitive and the l a t t e r i s constructed from pmgrmerdefined data types. Although not in the realm of c q u t a t i o w l linguistics, it does have a parallel, for exmple, in a function whi& inserts data into a semantic network and is expected t o handle various chunks of netwmk as well as atomic data. The data type might only be determined. during p r o p execution; using a generic function avoids distracting logic within the user's primary function. The section on functions as generators i s a l i t t l e weak from the point of view of computational linguistic requirements f a procedures which generate successive alterna?ives frcmn a complex s-tructure, f o r example, sentence parsing or referent resolution. The use of sjmple global variables is t m l M t e d in these contexts; one often heeds to become involved with saving the values of ~e~e r a l l w a l variables in special data blocks or stacking the decision pints associated with alternatives. The f i r s t is a well-known compiler-design technique, while h e second involves a backbxicking control struc'hxe. In fact, an excellent illustration of these ideas would be an implementation of the SfJOBOL4 pattern matohing system in SNOBON. Chapter 3 i s the m s t useful because it desmibes how propammer-defined data types can be used t o build \" s h . u~t u r e s~~: stacks, queues, l h k e d lists, binary trees, am3 trees. The s k i l l f u l user of such representations w i l l find a reduced role for complicated patterm mtchhg expressions because the implicit structure &coded into a string becomes d f e s t i n the explicit links of the s h c t u r e . Not only is there often an economic advantage, but the semmtics of SNOBOL4-are easier t o use than the implicit itcMracking semantics of pattern mtching. (Grimold himself p h t s this out i n the section on patterns as procedures. The prog~mner is encouraged t o consider economic trade-offs in the hplemehtation of stcuchuws. Often overlooked questions are addressed: f o r example, the relative merits of implementing stacks using s t r i n g s , arrays, tables, or defined data types. Programs for the use or traversal of structures are also provided. Although exercise 3.40 requests a representation f o r directed graphs, neither hint nor answer i s p v i d e d . The c a n p u t a t i d linguist having an h t e r e s t in s m t i c networks or similar associative structures is thus lef-t t o his own expert i s e . ?he basic -tree representation mst be significantly d i f i e d t o incorporate labelled edges, a nears of e a v e r s a l (search) t h m q h the edge set, and, of course, non-txee structures. Gritwold apologizes for not covering every application, but the generality and current popularity of networks f o r the representation of knowledge c a l l s for expanded treatment of the topic. Among the appSications covered in d e t a i l , the ones most relevant to ccsnputational linguistics include a Mndom sentence generator (fm a p r a~~~n a r ) , an mcm processor, and (perhaps) a context editor. The input and output of textual m t e r i a l is covered in depth undw d6cument p r e p m t i o n (Chapter 6). Since the text does not delve into computational linguisfics p w se, the reader (or instruct o r ) w i l l dften be called upon t o map techniques described in the text onto h i s own problem. I think that a g k d programer muld be able t o perform this 'transformation since solutions are provided f o r m y of the basic problems i n handling input t e x t , setting up data structures, and traversing these structmes . Before you begin programming your next computational linguistics project, a glance thr\"ough t h i s book my save you considerable programing time and reward you with usable and flexible data structures. Even i f you do not program in SNOBOL4, the techniques presented here might guide you t o more e f f i c i e n t usage of other languages. On the other hand, it might convince you t o try SNOBOLU.", "uris": null }, "FIGREF16": { "type_str": "figure", "num": null, "text": "practical guide for the occasional Fortran TV programmer to the basic \"tricks\" and vocabulary used by the systems programmers.", "uris": null }, "FIGREF17": { "type_str": "figure", "num": null, "text": "Schank and B.L. Nash-Webber, Eds., Theoretical Issuesoin Natural Language", "uris": null }, "FIGREF18": { "type_str": "figure", "num": null, "text": "OF THE FIFTH BUFFALO CONFERENCE ON COMPUTERS IN MEDICINE October 29-31, 1973 Published as t h e Journal of C l i n i c a l Computing Volume 3 , Number 2, September 1973Editor-In-Chief: E. R. Gabrieli", "uris": null }, "FIGREF19": { "type_str": "figure", "num": null, "text": "Schank and B.L. Nash-Webber, eds., Theoretiad1 Issues in Natural LanguageProcessing, 1975,. 20-23.", "uris": null }, "TABREF0": { "content": "
D. W. Grooms
National Technical Information Service
5285 Port Royal Rd.
Springfield, Virginia 22161
", "type_str": "table", "html": null, "num": null, "text": "" }, "TABREF1": { "content": "", "type_str": "table", "html": null, "num": null, "text": "" }, "TABREF2": { "content": "
W. C. Lin and T. L, Scully
case western Reserve University
Cleveland, Ohio
", "type_str": "table", "html": null, "num": null, "text": "Wrf ting. :" }, "TABREF3": { "content": "
T e i l 1:
fVortst3mme i n Grammar
", "type_str": "table", "html": null, "num": null, "text": "by conjoining remembered phrases. Productive processes have secondary roles of adapting old phrases to new situations and of gap filling.Description o f a program, written in machine language, that searches for words containing a fixed stem from Russian mathematical texts." }, "TABREF4": { "content": "
Semantics Tom Bye, Timothy Diller, and John Olney
System Development Corporation
Santa Monica, California 90406
Does not explain the
computation of values of compound expressions from the values of
features involved in a complete anal-
ysis are: average value, typical value, observed value, standard
deviation of values and polarity.
", "type_str": "table", "html": null, "num": null, "text": ", his assumptions, and his notational conventions are entered on this file. The data fields are: idenrifyhg number, document source, related sources, words analyzed, conventions, theoretlcal basis includingacknowledgements, assumptions, stated purpose, and limits, a SOLAR critique, and the name of the person responsible for the entry. This file is available via on-line queries or in a listing format. The file can be searched using the identifying-number on document source fields. Other fields can be searched using a string-matching facility." }, "TABREF5": { "content": "
Semantics -Discour-
PRIMITIVES AND WORDS
Yorick Wilks
Tstituto per Gli Studi
S-emantici e Cognitivli
Castagnola, Switzerland
Timothy Diller
System Development Corparation
in other SOLAR files. Thirty data tFelds are used, of which
Che following are searchable: author, year, index term, document
type, subject ID, document number, and Bell ID, Other fields can
be searched using a string-matching facility. This file available
via on-line queries or in a listing format including an mthor.
keyword and 'sequence number index.
", "type_str": "table", "html": null, "num": null, "text": "" }, "TABREF6": { "content": "", "type_str": "table", "html": null, "num": null, "text": "" }, "TABREF7": { "content": "
", "type_str": "table", "html": null, "num": null, "text": "" }, "TABREF8": { "content": "
Semantics -Discourse : Compreha46on
Her'bert H. Clark
Stanford University
Stanford, California
", "type_str": "table", "html": null, "num": null, "text": "this meaning representation, Another problem is that programs should not be designed to preserve all details, but then, what should be forgotten; point of view may be useful here" }, "TABREF9": { "content": "
Journal of Clinical Conlputihq, 3, 85-99, 1973
", "type_str": "table", "html": null, "num": null, "text": "Pratt, M. G. Pacak, M. Epstein and G. Dunham National Institutes of Health Division of Computer Research and Technology Bethesda, MarylandThe Systematized Nomenclature of Pathology (SNOP), in use at NIH, consists of about 15,000 entries in four lists: topography, morphology, etiology, and function. Only a few binary relations on terms are needed; e.g., location of morphology, (lesion) at topography (body site). Numerous relations on the primary relational triples evidently have to be defined." }, "TABREF10": { "content": "
Discourse : Expression
Neil M. Goldman
Information Sciences Institute
University of Southern California
Tn: R
", "type_str": "table", "html": null, "num": null, "text": "" }, "TABREF11": { "content": "
Teleos
Cambridge, Mass 02138
In: R
", "type_str": "table", "html": null, "num": null, "text": "In therapeutic discourse the subject is not so much generating discourse as regulating it. Statements are made, retracted, qualified and restated. The ERMA model simulates this. It has five stages, represented as CONNIVER contexts. The discourse stream has its source in a special program and then flows back and forth between the contexts before achieving its final expression. Each context determines suitability for expression; whether it should be censored or passed on with suggestions for modification. Concepts are represented by means similar to Minsky's frames. H . Clippinger , Jr ." }, "TABREF12": { "content": "
Wallace L. Chafe
Department of Linguistics
University of California
", "type_str": "table", "html": null, "num": null, "text": "" }, "TABREF13": { "content": "
contrOVersy Terry W i n o g r a d185
I 11, HIGHER LEVEL STRUCTURES
8. Notes on a schema for stories D a v i d E. R u m e l h a r t . 2 1 1
9. Tho structure of episodes in memory Roger C. s c h a n k -2 3
la. Concepts for representing mundane reality in plans
Robert P . A b e l s o n2 7 3
", "type_str": "table", "html": null, "num": null, "text": "Kuipers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ." }, "TABREF15": { "content": "
Eugene Charntak Institute for Semantic and Cognitive Studies Daniel G. KNOWLEDGE Castagnola, Switzerland
", "type_str": "table", "html": null, "num": null, "text": "" }, "TABREF16": { "content": "", "type_str": "table", "html": null, "num": null, "text": "" }, "TABREF17": { "content": "
", "type_str": "table", "html": null, "num": null, "text": "" }, "TABREF19": { "content": "
Computation : Pictorial systems
ON RETRIEVING INFORMATION FROM VISUAL IMAGES
Stephen Michael Kosslyn
The Johns Hopkins University
Baltimore, MD
In: R. Schank and B.L. Nash-Webber, Ed$., Theoretical Issues in Natural language
Processing, 1975, 146-150.
A computer graphics metaphor is useful for human visual ima-gery. Analogous oroperties are found: as objects become smaller
their constituent parts become more difficult to discern perceptual-
ly; as Computation : Pictorial systems
Zenon W. Pylyshyn
Department of Psychology
University of Western Ontario. * -. .
London, Canada
", "type_str": "table", "html": null, "num": null, "text": ". . . . . . . . . . . . . . . . -. . 39. . . . . , + . . . -. . . . . more parts are added to an image it becomes more degraded due to capacity limitations; image6 displaying more identifiable details take longer to construct; images cannot be indefinitely expanded before overflowing; and the existence of decay time for an image which affects the time taken to construct a riep Image." }, "TABREF20": { "content": "
CONFERENCE OPENING. Robert L. Ketter ' ' ' ' ' ' ' ' ' ' ' ' ' [Mbylicbkeiten der maschinellen Verarbeitung spatmittelhochdeutscher Texte. Berichht 8 Uber eln Forschungsunternehmenl T. Baumgarten Institute for ~ommunication Resegrch and Phofietics Bonn University CODING DATA Humanities : Concordance Computrsrs and the Humanities, 8 : 85-91, 1974
", "type_str": "table", "html": null, "num": null, "text": "EDITORIAL: COMPUTER-COMPATIBLE, STABLE AND CONTROLLED MEDICALVOCABULARY. E. R. Gabrieli . . . . . . . . . . . . . Durham . . . . . . . . . . . . . . . . . SOME PROGRAMMING ASPECTS OF NATURAL LANGUAGE DATA PROCESSING. William White . . . . . . . . . . . . . . . . AN ANTHROPOLOGICAL LINGUISTIC VIEW OF TECHNICAL TERMINOLOGY. Paul L, Garvin . . . . . . . . . . . . . . . COGNITIVE NETWORKS AND ABSTRACT TERMINOLOGY. David G. Hays . . 110 THE EVOLUTION OF A MEDICAL VOCABULARY. William D. Sharpe . . DIAGNOSES OF MEDICAL RECORDS: A CHALLENGE. J.v~n$gmond,andR.Wiem.e . . . . . . . . . . . . . . . . 130 RETRIEVAL-ORIENTED STORAGE OF MEDICAL DATA: OPERATIONAL ASPECTS. Charles W. Conaway ,and Edward T. O'Neill . . . . . 136 PROPOSED USE IN CANADA OF SNOMED IN A MEDICAL INFORMATION MANAGEMENT SYSTEM. Roger A. Cote . . . . . . . . . . . . . . 142 SECONDARY USERS OF CLINICAL RECORDS: AN OVERVIEW WilliamH. Kirby, Jr. . . . . . . . . . . . . . . . . . . . . 153 THE BUREAU OF DRUGS FOOD AND DRUG ADMINISTRATION, SCIENTIFIC INFORMATION SYSTEMS. Alan Gelberg . . . . . . . 155 DRUG PRODUCTS INFORMATION FILE. Frederick M. Frankenfeld . . MANAGEMENT SYSTEMS AT THE SOCIAL AND REHABILITATION SERVICES. WebsterA. Rogers . . . . . . . . . . . . . . . . 164 its period of greatest fruitfulness and to classical and patristic thought that passed through the schoolmen's filter. Space elso precludes discussion of the physical aspects of concordancing and printing, f o~ which Father Busa had the assistance of IBM. In a work of such vast proportiohs, the care of men cannot obviate error. Some 53 errors have been noted by the compilers in Conoordantia Prima. But even the correction of at least one of these contains a minor error: B.O12(QDV)23 13.ag8/8 should read B.012(QDV)22.13.ag8/8. See Sectio 2 vol-1, p. 526, co1.2. Also 12.Tabula Syntagmatum, the list of phrases concordanced under only one member of the phrase (pp.xiv-xvi) has at least two errors: bona esteriora should read bona exteriora (p. xiv): drosperitas terrena should read prosperitas terrena (p. xvi) The most useful pentaglot descriptive booklet of 46pp. is somewhat marred in the English version by misprints and verbal infeliaities. But these small matters are quite eclipsed by the enormous accomplishment of Father Busa and his co-workers." } } } }