The FINITE STRING, Volume 12, Number 3, continued

American Journal

of

Complltational

Linguistics

C U R R E N T

B I B L I O G R A P H Y

The selection of material through

the current second yeas of

AJCL's existence remains tentative. A survey

of

subscribes-

members will be included in the last packet mailed during 1975

to establish patterns of coverage for fdture years.

Categorization

Bf

entries deepens as the field defines itself

and the collection of literature against which new items can.

be

matched increases. The advice of members is welcome.

Many summaries are authors' abstracts, sometimes edited for

clarity, brevity, or completeness. Where possible, an infor-

mative summary

i.s

provided.

The Linguistic Documentation

Centre

of

the

University of

Ottawa provides many entries;

by

editorial accident, some

of the entries recently

received

from that

source

remain to

be included in

the next issue.

AJCL

gratefully adknowledges

the assistance of Brian Harris and his colleagues.

Some entries are reprinted with permission from Computer

Abstracts.

See the following frames for a kist of subject headings and

SUBJECT

HEADINGS

. . .

General

30

Phonetics

~honology

. . .

Recognition

34

Writing

. . .

Recognition

35

Lexicography

.

~exlcology

Dictiodary

. . .

37

. . .

Statistics

3.8

Grammar

Parser

. . .

38

. . .

Semantics

.

Discaurse

40

. . .

Comprehension

45

Expression

. . .

47

Memory

. . .

51

REPRESENTATION AND UNDERSTANDING

Linguistics

. . .

Methods

61

STRING A N D LIST PROCESSZNG I N SNOBOL41

TECHNIQUES AND

A P P L I C A T I D N S

By R a l p h E . Griswold

Reviewed b y Norman Badler

FORTRAN TEC-HNIQUES WITH S P E C I A L R E F E R E N C E T O NON-NUMEeICAt APPLICATIONS

By A . Colin Day

Reviewed b y Richard J. Miller

. . .

Information

structures

7 1

P i c t o r i a l

systems

. . .

72

Documentation

. . .

74

Indexing

. . .

7

8

Retrieval-

. . . , . . .

7

9

. . .

Thesauri

8

0

. . .

Management:

d l

. . .

Social-Behavioral Science

83

. . .

Humanities

84

XNDEX THOMISTICUS. S A N C T I THOMAE A Q U I N A T I S

Compilkd by Roberto BuSa, S. J.

A . r e V i e w of the first ten v ~ h m e s by Ford Lewis B a t t l e *

. . .

Cohcordance

90

. . .

. . .

Analysis

;

90

General

T H E O R E T I C A L

I S S U E S

I

4

I

N A T U R A L

L A N G U A G E

P R O C E S S I N G

AN INTERDISCIPLINARY WORKSHOP

IN

Cambridge, Massachusetts

June 10-13, 1975

EDITORS :

_

- _

_. --

Professor

R.

Schank

.Department

of

Camputar

science

Yale University

10

Hillhome

Avenue

and

New Haven, Connecticut 06520

B , L. Nash-Webber

Bolt

Eeranek and Newman Inc

50

Moulton

Street

Cambridge, Massachusetts

02138

AVAILABLE ~ O K :

Center for Applf ed Linguistics

1611 North

Kent

Street

Arlington, Virginia 22209

General.

-

T H E

P R A G U E

B u L ~ E T I N

O F

M A T H E M A T I C A L

L I N G U I S T I C S

Unive'rsi t a Karlova

Praha 1974

TABLE

OF CONTENTS

ON

VERBAL FRAMES

I N FUNCTIONAL GENERATIVE DESCRIPTION

. . .

P A R T I .

J.Panevova

3

STELLUNG

UND AUFGABEN

DER U E B R A I S C H E N LTNGUISTIK I

( E I N F U H R W G S S T U D I E ) . P .

Sgall

. . .

41

R E V I E W S

ALGEBRAIC LINGUISTICS IN

SOME

FRENCH SPEAKING COUNTRIES

(S.

Machova)

. . .

5

3

METODIKA

PODGOTOVKI

INF~RMATSIONMYKH

TEZAURUSOV

PEREV

s

VENGERSKOGO

POD

RED

I

PREDISLOVIEM

JU.

A .

SHREJDERA

V SB. PERSVODOV "NAUCHNO-TEKHNICHESWA INFORMATSIJA" VY;P

1 7 ,

1971

(T.

Ja.

Kazavchinskaja4

. . .

74

FORMAL LOGIC

AND

LXNGUISTICS,

Mouton, The

Hague,

1972

.

. . .

(0.

Prochazka)

E .

Zierer

,.

74

AUTOMATIC ANALYSIS

OF

DUTCH

COMPOUND

WOKDS,

Amsterdam

1972

W.

A .

Verloren

van

Themaat;

EXERCISES

IN

COMPUTATIONAL

LINGUISTICS,

Amsterdam

1970, I+.

Brandt

Cars-tius

General

C O M P . U T A T 1

O N A L

A N A L Y S E S

OF A S I A N

&

AFRICAN

LANGUAGES

A

new j,ournal

Mantaro

J.

Hashimoto,

E d i t o r

Project on Computational Analysis

National Inter-Universi t y Reseaxch Institute

of Asian & African Languages S; C u S l . t q r e s

4-51-21 Ni'shigahara, Ki t a k u , Tokyo 11 4 Japan

March,

1975

TABLE OF

CONTENTS

A

STATISTLC

STUDY

OF NAMES IN TAMIL INSCRIPTIONS

. . .

Noboru

Karashima

and

Y.

Sabbarayalu

3

IMPLICATIONS OF ANCIENT CHINESE WITROFLEY ENDINGS

Mantaro

5 .

Hashimoto

. . .

17

THE SINO-KOREAN READING

OF

KENG-SLIE

RIMES

MantaroJ,Hashimoto.

. . . ' . . .

25

"TO", "YUAN"

AND

"TE"-..

.A

COMPARISON

WITH

JAPANESE

. . .

Masayuki Nakagawa

31

LARYNGEAL

GESTUMS

AND THE ACOUSTIC CHARACTERISTICS

IN

HINDI

STOPS--PRELIMINARY

REPORT.

. . .

General

W i l l i a m A. Woods

Bolt Beranek and Newman

Inc.

Cambridge, Mass

02138

Report No. BBN 3067 April 1975

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 in4epen-

dent

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

net-

works, procedural semantics, s e l e c t i o n a l 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

In: R. Schank ahd B . L Nash-Webber, eds., Theoretical Issues i n Natural Language

Processing, 1975, 126-129;

Process

models

are

rigorous,

process

specifications

are

made

very e x p l i c i t , and complexity

ts

handled

by

use

of

computera.

A

methodology should be r e l i a b l e , e f f i c i e n t

and

have i n t e g r a t i v e

power. The d i s t i n c t i v e strengths

of

the c u r r e n l computer oriented

methodology

a r e

(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 d i v e r s i t y of hypotheses

can

be t e s t e d . Weaknesses are (a)

e x p e r b e n t s often take years

t o perform, (b) t h e a c t i v i t y i s t r e a t e d

as a programming exercise with the s t a t u s of data and program

un-

c l e a r l y defined

and

(c) i n attempting t o

be

general

on

a

p a r t i c u l a r

phenomenon, s i g n i f i c a n t others a r e missed.

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

General

W.

A.

Woods

Bolt Beranek and

Newrnan,

Inc

Cambridge,

Mass

In: R . Schank and B.L. Nash-Webbar eds. Theoreticel fssues in Natural Language Processing, 1 9 7 5 , 134-139.

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-indepen-

dent

'

language,

understanding theory.

Fof

theoretical studies,

a

methodology should

be cognitively efficient and should

deal

effect-

ively 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;

i s o l a t i o n

of

qomponents limits

scope. Intuition on human language performance is a good guide to

computational linguistics.

Phonetics -.Phonology

:

.Recognition

SPEECH

RECOGNITION

BY

COMPUTER

:

A

BIBLIOGRAPHY

WITH

ABSTRACTS

D.

W.

Grooms

National Technical Information

Service

5285

Port Royal Rd.

Springfield, Virginia

22161

R e p o r t No. Corn-74-21435/6, September 1974. Price: $20.00

Contains

142

abstracts covering recognition, synthesis,

and

Writing

-

Recognition

-

FUZZY

LOG

l

C FOR HANDWRITTEN NUMERICAL CHARACf

ER

RECOGNITION

P.

Siy

and C.

S.

Chen

Akron University

IEEE Transactions on Systems, Man and Cybernetics, $Me-#! 570-575, 1 9 7 4

considers c h a r a c t e r s

a s

a d i r e c t e d 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 f e a t u r e s which a r e

t r e a t e d

as

fuzzy

v a r i a b l e s .

A

c h a r a c t e r i s represented by

a

fuzzly

function

which

r e l a t e s

its fuzzy v a r i a b l e s , and by t h e 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.

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

A

16:l compaction r a t i o was achieved by s t o r i n g only t h e 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

exem-

Writing

:

Reco-gnitian

A

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

Computers and the Humanities 9, 1: 13-24, 1975

Various proposals

are

discussed, p r i n c i p a l l y (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 e x p l i c a t e s the order, with

a recursive d e f i n i t i o n of

subframes

.

(2)

Fuj

imara

has

an inven-

tory

of strokes

and

operators. For

each

s t r o k e

3 functional

points

are

i s o l a t e d and operators define

the linking

by

reference

t o these points. Applications include keyboard i n p u t , storage

and r e t r i e v a l o r characters,

and

automatic recognition. There

a r e 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.

Writing

:

Recognition

₃₆

LHINESE

CHARACTER

RECOGNlTION

BY A

STOCHASTIC SECTIONALGRAM

METHOD

Y-L.

Ma

National Taiwan

University

IE6E Transactions on Systems, Man and Cybernetics, SEIG-4; 575-584, 2974

An

approach

t o recognition

of a

block

p i c t u r e

by

comparing

it

with s t o c h a s t i c 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

be-

tween

t h e

stroke-occurrence p r o b a b i l i t i e s

of

corresponding quanta

i n

t h e

two sectionalgrams a r e

summed one

of

these

two

s e c t i o n a l -

grams

being

derived

from t h e

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 ,

Wrf

ting.

:

Recognition

COMPUTER

IDENTIFICATION

OF

CONSTRAINED

HAND PRINTED

CHARACTERS

WITH

A

HIGH RECOGNITION

RATE

W.

C.

Lin

and T. L, Scully

case western Reserve University

Cleveland, Ohio

IEEE Transactions on Systems, Man end Cybernetics, SMC-4, 497-504, 1974

Hand printed o n a standardizing grid made of

twenty

line seg-

ments, yielding twenty features,

and input using a television camera,

49 character classes were recognized at a greater than

99.4%

rate.

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.

Lexicoqraphy

-

Lexicology.

:

Dictionary

Joseph

D.

Becker

Zn: R . Schank and B . 5 . flash-Webber, e d s . , Theoretical Issui?s i n Natural Language

Processing, 1975, 611-63.

We

speak

mostly by

conjoining remembered

phrases.

Productive

Lexico~raphy

-

Lexicolopy

: Statistics

PROGRAMS

FOR

LINGUISTIC STATISTICS

PART

1:

WORD

ROOTS

IN

S C I E N T I F I C

A N D TECHNICAL

RUSSIAN

[Programme zur S p r a c h s t a t i s t l k . T e i l 1 :

fVortst3mme i n russf-schen natunrissenschaftlichen und technischen.Fachsprachen]

S. Halbauer

Angewandte Informatlk, 1 6 : 469-470, 1974

Description

o f

a

program, written in machine language, that

searches for words containing

a fixed stem

from

Russian mathematical

texts.

Grammar : Parser

George

E.

Heidorn

Computer Sciences Dept.

IBM

Watson

Research Center

Yorktown

Heights,

'NY

In R. Schank and B . L . Nash-Webber, was., Theoretical Issues i n Natural Language

Processing, 1-5, 1975.

Gramar

:

Parser.

DIAGNOSPS

AS .A NOTION OF GRAMMAR

Mitchell

Marcus

Artificial Intelligence Laboratory

Massachusetts Institute of Technology

Cambridge

In R. Schank and B . L . Nash-Webber, e d s . , 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 re-

k

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 struc-

ture constructed

to

date,

and

makes

whatever substructures

it

can

from the remaining part.

Grammar : Parser

William White

National

I n s t i t u t e s

of Health

Divislon

of

Computer

Research

and Technology

Bethesda, Maryland

Journal of C l i n i c a l Computing, 3, 180-102, 1973

A morphological analyzer is written in P L / ~ using a recursive

macro

actuated

generator.

Called with

a

word

as argument i t

returns

a s k e m , part of speech, possible transformations, and semantic infor-

Semantics

-

D i s c o u r s e

B r i a n P h i l l i p s

Department of Information E n g i n e e r i n g 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 Y o r k , 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

s h ~ w n

t h a t p r o p o s i ~ i o n s of

a

c o h e r e n t d i s c o u r s e must be l o g i c - a l l y cbnnected and e x h i b i t a h i e r a r c h i c t h e m a t i c s t r u c t u r e t h a t

h a s a s i n g l e r o o t . A n eqample of a l o g i c a l c o n n e c t i v e i s ' C a u s e ' ;

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 . , ' p o i s o n ' 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 c a u s e s

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

c o h e r e n t d i s c o u r s e i s

i t s

m a t r i x theme; a n 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

e x p r e s s e d . If o m i t t e d , 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 s t o r e of

world knowledge

-

e n c y c l o p e d i c knowledge. A n e n c y c l o p e d i a i s d e s -

c r i b e d t h a t c o n t a i n s a l l t h e d e v i c e s r e q u r s e d 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 e n c y c l o p e d i a 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 c o g n S t i v e

t a s k s . The e n c y c l o p e d i a i s a d i r e c t e d g r a p h . C a t e g o r i e s of nodes

Semmtics

-

Discourse

ON

" F U Z Z Y ~ ADJECTIVES

Fred J. Damerau

IBM Watson Res~arch

Center

Yorktown Heights,

N

.Y

.

Repqrt No. RC 5340 March 2 7 , 1975

Discusses some of the problems that arise

when

the concept

of a linguistic

v a t i a b l e

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. Does not explain the

computation

of values

of

compound expressions from the values of

their

components.

Not

all

adjectives

can be

related

LO

an under-

lying numerical

base.

Other features involved

in a complete anal-

ysis are:

average

value, typical value, observed value, standard

deviation of values and polarity.

[Dl'stribution l i m i t e d prior to publication 6 ]

Semantics

-

Discburse

USER'S

GUIDE

TO THE

SOLAR

THEORETICAL BACKGROUNDS F I L E

Timothy Diller and Tom Bye

System Development Corporation

Santa Monica, California

90406

Report No. TM-5292/002/00 April 1975

For

each

analysis in the

semantic

analysis

file the author's

theoretical orientation,

his

assumptions, and his notational conven-

tions

are

entered on

this file. The data

f i e l d s

are: idenrifyhg

number,

document source, related

sources,

words analyzed, conventions,

theoretlcal basis including

-

acknowledgements,

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

Semantics

-

Discourse

USER

S

GUIDE

TO

THE

SOUR

SEMANTIC

ANALYSIS

FILE

Tom

Bye, Timothy Diller, and John

Olney

System Development Corporation

Santa Monica, California

90406

Rdgort No. ~M-.5292/001/01) April 1975

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.

Semantics

-

Qiscourse.

USER'S

G U I D E

TO

THE

SOLAR

BIBLIOGRAPHY

F I L E

Timothy Diller

System Development Corparation

Santa

Nonica, California

90406

Report No. TM-5292/000/02 December 1974

This file

provides

the citations

to

the

documents r a e r -

Semantics

-

Discour-

PRIMITIVES

AND

WORDS

Yorick Wilks

Tstituto per Gli Studi

S-emantici

e

Cognitivli

Castagnola, Switzerland

3n R. Schank and B.L. Nash-Webber, ds., Thearetical Issues i n Natural Language

Processing, 1975, 38-41.

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.

Semant,ics

-

Discourse

META-COMPILING

TEXT GRAMMARS AS A

MODEL

FOR HUMAN

BEHAVIOR

Sheldon Klein

Computer Sciences Department

University of Wisconsin

Madison

In: R . Schank and B.L. Nash-Webb-, eds., Theoretical Zssues in Natural Language

Processing, 1975, 84-88.

Semantics

-

Discourse

RQger C

.

Schank

Yale University

New

Haven,

Connecticut

Irl R. Schank and B.L. Nash-Webber, eds., Theoretical Issues in Natural Language

Processing, 1975, 34-37.

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,

trans-

fer of physical location;

MTRANS,

transfer of information;

PROPEL,

application of physical force;

M13UILD

construction of new contep-

tual 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.

An

analysis of

the

verb

'hand' is paraphrased

as:

'S

had

Semantics

-

Discours.@

A

SYSTEM OF

SEMANTIC PRIMITIVES

b y

Jackendoff

Department

of

English Brandeis Univefsity

In R. 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 in- terprecations. 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.

Comprehension is a memory process; breaking computational under standing into sccbyrob-leem

af

parsirig

and semantic

iktetpre- tation has hindered progress with

much

effort wasted

on

the con- struction

of

parsers.

A

system is described

in

which a monitor takes words from a sentence one at

a

time, from left to

right.

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 expecta-

Semantics

-

Discourse

:

Comprehension

Robert

P.

Abelson

Yale University

New Haven Connecticut

In: R. Schank and B.L. Hash-Webber, Eds., Theoretical Issues in Natural Language

Processing, 1975, 140-143.

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.

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

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

Semantics

-

Discourse

:

Compreha46on

Her'bert

H. Clark

Stanford University

Stanford, California

In; A. Schank and B.L. Nash-Webber, Eds., Theoretical Issues in Nataz-a1 Language

Processing, 1975, 169-174.

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

t h a t

he will

not already have

the

new

in-

formation attached to

the

antecedent. Inference mechanisms include

direct reference, identity, pronominalization, epithets, set member-

ship,

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

assump-

tions. Both

backward

and forward inferences are possible,

but

only

Semantics

-

Discourse

:

Comprehension

COMPUTERS

AND

NATURAL

LANGUAGE

A.

Y.

Pratt,

M. G.

Pacak, M. Epstein and

G.

Dunham

National Institutes

of Health

Division of Computer Research and Technology

Bethesda,

Maryland

Journal of Clinical Conlputihq, 3, 85-99, 1973

The 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

topog-

raphy (body site). Numerous relations on the primary relational

triples evidently have to be defined.

Semantics

-

Discourse :

Expression

Bertram

C.

Bruce

Bolt

Beranek

& Newman

Cambridge,

Mass

02138

In: R. Schank and B . L . Nash-webber, eds., Theoretical Issues ih iVatural. tanguage Processing, 1975, 64-67.

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)

establish-

ing presuppositions, (ii)

by linguistic conventions, and (iii) by

discourse structure. kSoc*al Actioii

Paradigm

is a model of the

Semantics

-

Discourse

:

Expression

Neil

M.

Goldman

Information Sciences Institute

University

of

Southern

California

Tn: R. Schank and B . L . Nash-Webber, e d s . , Theoretical Issues i n Natural Language

Processing, 1975, 74-78.

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 mat-

ching mechanism,

a

discrimination net.

The

case

framework of verbs

is one source of knowledge for choice of syntactic structure.

Semantics

-

Discourse : Expression

SPEAKING

WITH MANY TONGUES: SOME

PROBLEMS

IN MODELING SPEAKERS

OF ACTUAL DISCOURSE

John

H.

Clippinger,

Jr,

Teleos

Cambridge,

Mass

02138

In: R. Schank and B . L . Nash-Webber, e d s . , Theoretical Issues i n Natural Language

Processing, 1975, 68-73

In

therapeutic discourse the subject is not so

much

gener-

ating 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 expres-

Semantics

-

Discourse :

Expression

CONSIDERATIOP~S

FOR COMPUTATIONAL

THEORIES OF

SP6AKING

:

SEVEN THINGS

SPEAKERS

DO

John

H

.

Clippinger

,

Jr

.

Teleos

Cambridge, Mass 02138

In: R. Schank and B.L. Nash-Webber, e d s . , Theoretical I s s u e s . i n Natural b n g u a g e Processing, 3975, 122-125.

Technological computational linguistics is primarily con-

cerned with software technology whereby computers can

use and pro-

cess 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.

Semantics

-

Discourse :

Expression

CREATIVITY

I N VERBAL1

Z A T l O N

AS

EVIDENCE

FOR

ANALOGIC KNCIWLEDGE

Wallace

L. Chafe

Department of Linguistics

University

of California

Berkeley

Iq: R . Schank and B . L . dash-Webber, E d s . , Theoretical IsSues i n Natural Language Processing, 1975, 144-145.

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

e d i t e d b y

D a n i e l G . Bobrow Allan Collins

Xerox

P a l o

Alto Research

Center Bolt Beranek

and

N e w a n

P a l a Alto, California Cambridge, Massachusetts

A c a d e m i c P r e s s

1 9 7 5

Dedicated to the memory of

JAIME

CARBONELL,

1928-1973

1. ~ i m e n s i o n s

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 5

3. Reflections on the formal description of behavior

J 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 R o b e r t 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

! ~ E W 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

Semantics

-

Discourse : Memory

7 . Frame representations and the declarative-procedural

. . .

contrOVersy Terry W i n o g r a d 185

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

R o g e r C. s c h a n k - 2 3 7

la. Concepts for representing mundane

reality

in plans

Robert P . A b e l s o n

. . .

2 7 3

I V ,

SEMANTI

c

KNOWLEDGE

I N

UNDERSTANDER

SYSTEMS

11. Multiple representations of knawledge for tutorial reasoning John S e e l y Brown and R i c h a r d R . B u r t o n

.

3 1 1

12. The role of

semantics

in

automatic! speech understand- ing Bonnie N a s h - W e b b e r

. . .

3 5 1

13. Reasoning from incomplete knowledge A l l a n C o : l i n s ,

E l e a n o r H . W a r n a c k , N e l l e k e A i e l l o , and Mark L .

M i l l e r .

. . .

3 8 3

REPRESENTATION

AND

UNDERSTANDING

P r e f a c e

J a i m e Carbonell was our f r i e n d and colleague. For many years h e worked w i t h 11s on problems i n A r t i f i c i a l

Intelligence, especially o n t h e developrnerit of RII i n t e l l i g e n t

instructionnl system. Jainle directed t h e Artificinl

Intelligence group e t Bolt, Deranek, and Ncwman ( i n Cambridge, Massnchusetts) u n t i l h i s d e a t h i n 1973. Some

of

u s who hod worlred with J a i m e decided to hold a

conference i n his nlemory, a confcrerlce whose guiding principle wonld be t h a t J a i m e would have enjoyed it. T h i s book is t h e r e s u l t of t h a t conferencb.

J a i n ~ e Carbonell's isnportant c o n t r i b u t i o n to cognitive science i s best sumnlarized i n t h e t i t l e 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 I n s t r u c t i o n (CAI) systems. H e dreamed of a system which h a d a data base of knowledge about a topic m a t t e r and general information a b o u t language and t h e principles of t u t o r i a l instruction. T h e system could t h e n pursue a n a t u r a l t u t o r i a l dialog w i t h a student; sometimes following the student's initiative, sometimes t a k i n g i t s own i n t i a t i v e , b u t always generating i t s statements rind responses i n a n a t u r a l way from i t s general knowledge. T h i s system contrasts s h a r p l y w i t h existing systems f o r Computer-Assisted I n s t r u c t i o n 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 f u l l realization of t h e dream.

It was a pleasure t o work w i t h J a i m e . H i s kindness and h i s enthusiasm were infectious, and t h e discussions we h a d w i t h h i m over t h e y e a r s were a g r e a t s t i m u l u s t o o u r own thinking. Both as a friend a n d a colleague we miss h i m greatly.

Cognitive Science. T h i s book contains studies in a n e w

REPRESENTATION AND UNDERSTANDING

of questions. In recent years, t h e interdctions among the workers i n 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$ t h a t 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 t h a t t h i s book can serve as an illustrntion of t h e type of problems Chat can be q q ~ r o a c h e d through interdisciplinary cooperation. The participants i n t h i s book (and a t 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.

Subject Matter. The book contains four sections. In the first section, Theory of R e p r e s e n t o t i o n , general issues involved i n 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 t h e 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 t h e input drrta in the context of a larger structural organization, and which answers questions about t h e situation based only on the contingent knowledge structure.

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 i n p u t data and to h y p o t h c s ~ s about structure. Benjamin J. Kuipers describes t h c c o n c ~ l ) t of a frame us a structural organizing u n i t f o r data ele~nents, nnd

he discusses t h e use of these u n i t s in the context of n

recognition system. Terry Winogrod explores issues i~lvolved in t h e controversy on r c l ~ r c s c ~ l t i n g knowledge i u

declarative vcrsus procedural form. W i n o g r ~ t l uses t h e concept of a frame ns a basis for the synthesis of t h e declarative and proccdural tipproaches. The frame provides a n organizing structure on which to attach both declarative and procedural informhtion.

T h e third section, l l i g h e r L e v e l S t r u c t u r e s , focuses on t h e representation of plans, episodes, and stories w i t h i n memory. David E. Rumelhart proposes a grammar f o r well- formed stories. 'His summarization rules for stories based on t h i s grammar seem to provide reasonable predictions of

human behavior. Roger C. Schank postulates that i n

understanding paragraphs, t h e reader fills in causal connections between propositions, and t h a t such causally linked chains are t h e basis f o r most human memory organization. Robert P Abelson defines a notation i n

which to describe t h e intended effects of plans, a n d to express the conditions necessary f o r achieving desired states. T h e f o u r t h section, Semantic K n o w l e d g e i n U n d e r s t a n d e r S y s t e m s , describes how knowledge h a s been used i n existing systems. J o h n Seely.Brown a n d Richard R.

B u r t o n describe a system which uses multiple representations to achieve expertise i n teachiog a s t u d e n t a b o u t debugging electronic circuits. Bonnie Nash-Webber describes t h e role played by semantics in the understanding of continuous speech i n a limited domain of discourse. Allan Collins, Eleanor H. Warnock, Nelleke Aiello, and

Mark

L.

V i l l e r describe a continuation of work o n J a i m e Carbonell's SCHOLAR system. They examine how liumans use strategies to f i n d reasonable answers to questions f o r which they do n e t have the knowledge to answer w i t h certainty, and how people can be t a u g h t t o reason t h i s way.

REPRESENTATION AND

UNDERSTANDING

Acknowledgments. We a r e g r a t e f u l for t h e h e l p of o largo number of people who made t h e conference a n d this book possible. T h e conference partici.pants, n o t all o f whom a r e represented i n t h i s book, created a n atmosphere i n which interdisciplinary exploration became a joy. T h e people attending were:

From Bolt Beranek a n d Newman--Joe Backer, Rusty Bobrow. J o h n Brown. Allan Collins. Bill Merriam. Bonnie - .

ash-~ebber,

lea no;

Warnock, a n d - R i l l Woods. . From Xerox Palo Alto Research Center--Dan Bobrow, Ron Kaplan, S h a r o n K a u f n ~ a n , J u l i e L w t i g , a n d T e r r y Winograd from Stanford University).

From t h e University of Cnlifowia, S e n Diego--Don

Norman and Dave Rumelhart. From t h e University of Texas--Bob Simmons. From Yale University--Bob Abelson. From Uppsala University--Eric Sandewall.

J u l i e Lustig made all t h e arrangements f o r t h e conference a t Pajaro Dunes, and was largely responsible f o r making i t a comfortable atmosphere i n which to discuss some very difficult tecllnical issues. Carol Van Jepmond was responsible f o r typing, editing, a n d formatting t h e manuscripts t o meet t h e specifications of t h e pysterns used i n the production of t h i s book. I t is t h a n k s to h e r skill

a n d effort t h a t t h e book looks a s beautiful as i t does. J u n e S t e i n did t h e f i n a l copy editing, made general corrections, and gave many valuable suggestions on f o r m a t a n d layout.

Photo-ready copy was produced w i t h t h e a i d of e x p e r i m e n t d formatting, illustration, a n d p r i n t i n g systems

built a t t h e Xerox Palo Alto Research Center. We would l i k e to thank M a t t Heile-r, Ron Kaplan, Ben Kuipers,

William Newman, Ron Rider, Bob Sproull, a n d Larry Tesler f o r their h e l p in making photo-ready production of t h i s book possible. We a r e grateful t o t h e Computer Science Laboratory of t h e Xerox Palo Alto Research Center f o r making available t h e experimental facilities and f o r i t s continuing support.

Daniel G. Bobraw Allan

M.

Collins March 1975

Semantics

-

Discourse : Memory

KNOWLEDGE

Eugene Charntak

Institute for Semantic and Cognitive Studies Castagnola,

Switzerland

In R. Schank, and B.L. Mash-Webber, eds., Theoretical Issues in Natural Language

Processing, 1975, 62-51.

Frames

are static structures about one stereotyped topic

Each

frame

has many statements about

the

topic, each expressed in

a

suitable

semantic

representation.

The

primary

goal in under- standing

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.

Semantics

-

Discourse : Memory

COGNITIVE

NETWORKS AND ABSTRACT TERM1 NOLOGY

N avid

G. Hays

Department of Linguistics

State University of New York at Buffalo

J o u r n a l o f C l i n i c a l Computing, 3 , 110-118, 1973

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

Semantics

-

Discourse

: Memory

Ronald~J.

Brackman

Center for Research in Computing Technology

Harvard University

Cambridge, Mass

02138

Report No. TR 6-75.

A

data

structure scheme for creating structured concept

nodes

tn

a semantic network is presented, with structuring tech-

niques based op

a

set of primitive

link

types including:

defined

as attribute part, modality, role, structural/condition, valuelre-

striction, subconcept and superconcept. This structure will atore

descriptions of bibliographic references in a

way

that

will facili-

tate 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.

Semantics

-

Discourse

: Memory

A

FORMALISM FOR RELATING L E X I C A L AND PRAGMATIC INFORMATI ON: I T S RELEVANCE TO RECOGNITION AND GENERATION

Aravind

K.

Joshi and Stanley

J.

Rosenschein

The Moore School

of

Electrical Engineering

University of Pennsylvania

Philadelphia,

19174

In: R. 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

pro-

cedura

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 Language

Processing, 1975, 55-60.

The distinction between semantic and episodic memory is not

so

much

one

between different kinds of memo

,

but one between dif-

'K

ferent kinds

of

knowledge.

The dbtinction as been rejected, be-

cause

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

Semantics

-

Discourse

:

Memory

~CTD-MOUTH

ING

FRAMES

Jerry Feldman

University

of

Rochester

New

York

In: R . Schank and B.L. Nash-Webber, eds., Theoretical Issues in Natural knguage

Processing, 1975, 92-93.

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 de-

fault 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.

Semantics

-

Discourse : Memory

SOME

THDUGHTS

ON

SCHEMATA

Wallace

L.

Chafe

Untvers

it!y

of ~aligornia

Berkeley

In: R . Scharik and B.L. Bash-Webber, eds., Theoretical Issues i n Natural Language Processing, 1975, 89-91.