Fourth Conference
o n
Applied
Natural Language
Processing
Association for
C o m p u t a t i o n a l Linguistics
Proceedings of the Conference
1 3 - 1 5 O c t o b e r 1 9 9 4
S t u t t g a r t , G e r m a n y
Q1994, Association for Computational Linguistics
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P R E F A C E
This volume represents the fourth proceedings of an "ACL Applied" conference. The contents of these pages illustrate some of the changes that have influenced us since the first such conference in 1983: a heightened emphasis on applications and commercial enterprise, integration of natural language processing with other technologies, and the emergence of innovative new applications and methods. The pace of change in the field has become so rapid t h a t the c o m m u n i t y felt a need to have an applied conference on a regular basis; hence, this conference follows the third by only two years.
Never has the interplay between computational linguistics and applications been so active and harmonious. Emerging applications and even emerging commercial successes have driven research, for example, in multimedia systems, information retrieval, lexical representation, multi-lingual tools, and document processing. New methods in turn have led to improved applicability and commercial viability. The work reported here falls on both sides of an i m p o r t a n t boundary: the "technology push" that helps to create applications and markets, and the "market pull" t h a t guides research and development, creates funding, and heightens the excitement in the field.
The process by which this proceedings has been created reflects some of the same changes that have driven the research. Much of the preparation, review, revision, and final transmission of the papers was done electronically, leading to the rapid, easy, and accurate exchange and reproduction of materials between points as distant as North America and Asia, as well as Eastern and Southern Europe. The same worldwide connectivity that makes this possible is also responsible for some of the advances in the field as well as for some emerging applications.
A number of people deserve special recognition for their contribution to this effort. Trisha Yannuzzi of the Institute for Research in Cognitive Science and Craig Reynolds of the GRASP Laboratory at the University of Pennsylvania helped to coordinate the program committee activities as well as the preparation of the proceedings, with help from Jodi Kerper and others at IRCS. Uwe Reyle, along with Christian Rohrer and others in S t u t t g a r t , made the conference arrangements and did publicity as well as the cover layout. Fernando Pereira, Karen Sparck Jones, and others in the ACL provided logistical as well as moral support. These individuals contributed to a global, integrated project representative of the current state of the art.
Paul Jacobs, P r o g r a m Chair Philadelphia, Pennsylvania September, 1994
S P O N S O R S
Association for Computational Linguistics
Gesellschaft ffir Informatik
IBM
LAPP-Kabel
Robert-Bosch-Stiftung
Landesgirokasse
Sun Microsystems
P R O G R A M
C O M M I T T E E
Susan Armstrong
Harry Bunt
Jim Cowie
Ido Dagan
Robert Ingria
Paul Jacobs, Chair
Richard Kittredge
Kazunori Muraki
Peter Norvig
Hans Joachim Novak
Martha Palmer
Manny Rayner
Donia Scott
Oliviero Stock
Annie Zaenen
A D D I T I O N A L
R E V I E W E R S
Laurent Bourbeau
Rebecca Bruce
Fabio Ciravegna
Barbara Di Eugenio
Ted Dunning
David Farwell
Sebastian Goeser
Steve Helmreich
Wanying Jin
Jutta Kreyss
Alberto LaveUi
Mark Liberman
Cecile Paris
Fabio Pianesi
Emanuele Pianta
Richard Power
Graham Russell
Carlo Strapparava
Jan Wiebe
T A B L E O F C O N T E N T S
T e x t
Generation
Bilingual Generation of Job Descriptions from Quasi-Conceptual ~brms
David E. Caldwell & T a t i a n a Korelsky . . . 1
Practical Issues in Automatic Documentation Generation
K a t h l e e n M c K e o w n , K a r e n Kukich & J a m e s Shaw . . . 7
D o c u m e n t Image Understanding
Language Determination: Natural Language Processing from Scanned Document Images
P e n e l o p e Sibun & A. Lawrence Spitz . . . 15
Modeling Content Identification from Document Images
T a k e h i r o N a k a y a m a . . . 22
Machine Translation
( M e t h o d s )Machine Translation of Sentences with Fixed Expressions
N a o t o K a t o h ~z T e r u a k i Aizawa . . . 28
Termight: Identifying and Translating Technical Terminology
Ido D a g a n & Ken C h u r c h . . . 34
Symmetric Pattern Matching Analysis for English Coordinate Structures
Akitoshi O k u m u r a &: K a z u n o r i M u r a k i . . . 41
Tagging Models
Tagging Accurately -- Don't Guess If You Know
Pasi T a p a n a i n e n & A t r o Voutilainen . . . 47
Does Baum- Welch Re-estimation Help Taggers?
David E l w o r t h y . . . 53
Improving Language Models By Clustering Training Sentences
David C a r t e r . . . 59
Text Processing
Exploiting Sophisticated Representations for Document Retrieval
Steven Finch . . . 65
Combination of Symbolic and Statistical Approaches for Grammatical Knowledge Acquisition
Masaki K i y o n o & J u n ' i c h i Tsujii . . . 72
Adaptive Sentence Boundary Disambiguation
David D. P a l m e r & M a r t i A. H e a r s t . . . 78
Acquiring Knowledge from Encyclopedic Texts
F e r n a n d o G o m e z , Pdchard Hull 8z Carlos Segami . . . 84
Machine Translation
( S y s t e m s )A Successful Case of Computer Aided Translation
Three Heads Are Better Than One
R o b e r t F r e d e r k i n g & Sergei Nirenburg . . . 95
Real-Time Spoken Language Translation Using Associative Processors
K o z o Oi, Eiichiro S u m i t a , O s a m u Furuse, Hitoshi Iida & T e t s u y a Higuchi . . . 101
Robust Parsing
Yet Another Chart-Based Technique for Parsing Ill-Formed Input
T s u n e a k i K a t o . . . 107
Recycling Terms into a Partial Parser
C h r i s t i a n J a c q u e m i n . . . 113
Interface Applications
Resolving Anaphora in a Portable Natural Language Front End to Databases
F l a v i a A. B a r r o s ~ A n n e Deroeck . . . 119
Upholding the Maxim of Relevance during Patient-Centered Activities
Abigail S. G e r t n e r , Bonnie L. W e b b e r & J o h n R. Clarke . . . 125
The Delphi Natural Language Understanding System
Madeleine B a t e s , R o b e r t B o b r o w , R o b e r t Ingria & David Stallard . . . 132
Understanding Location Descriptions in the Lei System
D a v i d N. Chin, M a t t h e w M c G r a n a g h a n & T u n g - T s e Chen . . . 138
Lexical Processing
Tagging and Morphological Disambiguation of Turkish Text
K e m a l Ofiazer ~¢ Ilker K u r u S z . . . 144
A Robust Category Guesser for Dutch Medical Language
P e t e r Spyns . . . 150
Handling Japanese Homophone Errors in Revision Support System for Japanese Texts; Revise
M a s a h i r o O k u . . . 156
Text Categorization and Retrieval
A Probabilistic Model for Text Categorization: Based on a Single Random Variable with
Multiple Values
M a k o t o I w a y a m a K: T a k e n o b u T o k u n a g a . . . 162
Robust Text Processing in Automated Information Retrieval
T o m e k Strzalkowski . . . 168
Might a Semantic Lexicon Support Hypertextual Authoring?
R o b e r t o Basili, Fabrizio Grisoli ~ M a r i a T e r e s a P a z i e n z a . . . 174
Posters
Improving Chinese Tokenization with Linguistic Filters on Statistical Lexical Acquisition
Dekai W u & P a s c a l e Fung . . . - . . . 180
Reference Resolution in Newspaper Articles
T a k a h i r o W a k a o . . . 182
Automatic Acquisition of Semantic Attributes for User Defined Words in Japanese to English
Machine Translation
~:~
S a t o r u I k e h a r a , Satoshi Shirai, Akio Yokoo, Francis B o n d & Yoshie Omi . . . 184
Degraded Text Recognition Using Word Collocation and Visual Inter-Word Constraints
T a o H o n g & J o n a t h a n J. Hull . . . 186
Using Syntactic Dependencies for Word Alignment
Fathi Debili, E l y , s S a m m o u d a ~: A d n a n e Zribi . . . 188
English Adverb Generation in Japanese to English Machine Translation
K e n t a r o O g u r a , Francis B o n d & S a t o r u I k e h a r a . . . 190 : :
A Practical Evaluation of an Integrated Translation Tool During a Large Scale Localisation
Project
R e i n h a r d Sch£1er . . . 192 ;: ~
Spelling Correction in Agglutinative Languages
K e m a l Oflazer ~: C e m a l e d d i n Gfizey . . . 194 ~
Integration of Example-Based Transfer and Rule-Based Generation
S u s u m u Akamine, O s a m u Furuse ~: Hitoshi Iida . . . 196 •
An Evaluation of a Method to Detect and Correct Erroneous Characters in Japanese Input
Through an OCR Using Markov Models
T e t s u o Araki, S a t o r u Ikehara, N o b u y u k i T s u k a h a r a & Yasunori K o m a t s u . . . 198
Multifunction Thesaurus for Russian Word Processing
Igor A. Bolshakov . . . 2 0 0 "
Representing Knowledge for Planning Multisentential Text
Jose Coch & R a p h a e l David . . . 203 -
Guided Sentences Composition for Disabled People
R o b e r t P a s e r o , N a t h a l i e R i c h a r d e t & P a u l S a b a t i e r . . . 205
An Interactive Rewriting Tool .for Machine Acceptable Sentences
IIideki Hirakawa, Kouichi N o m u r a & Mariko N a k a m u r a . . . 207
TECHDOC: Multilingual Generation of Online and OJZfline Instructional Text
D i e t m a r RSsner & M a n f r e d Stede . . . 209
An Inheritance-Based Lexicon for Message Understanding Systems
L y n n e J. Cahill . . . 211
Industrial Applications of Unification Morphology
G £ b o r PrSsz~ky . . . 213
Sublanguage Engineering in the FoG System
R i c h a r d K i t t r e d g e , Eli Goldberg, M y u n g h e e Kim & Alain Polguhre . . . 215 ~
A U T H O R I N D E X
A i z a w a , T e r u a k i . . . 28
A k a m i n e , S u s u m u . . . 196
A r a k i , T e t s u o . . . 198
B a r r o s , F l a v i a A . . . 119
Basili, R o b e r t o . . . 174
B a t e s , M a d e l e i n e . . . 132
B o b r o w , R o b e r t . . . 132
B o l s h a k o v , I g o r A . . . 200
B o n d , F r a n c i s . . . 184, 190 C a h i l l , L y n n e J . . . 211
C M d w e l l , D a v i d E . . . 1
C a r t e r , D a v i d . . . 59
C h e n , T u n g - T s e . . . 138
C h i n , D a v i d N . . . 138
C h u r c h , K e n . . . 34
C l a r k e , J o h n R . . . 125
C o c h , J o s e . . . 203
D a g a n , I d o . . . 34
D a v i d , R a p h a e l . . . 203
D e b i l i , F a t h i . . . 188
D e R o e c k , A n n e . . . 119
E l w o r t h y , D a v i d . . . 53
F i l g u e i r a s , M i g u e l . . . 91
F i n c h , S t e v e n . . . 65
F r e d e r k i n g , R o b e r t . . . 95
F u n g , P a s c a l e . . . 180
F u r u s e , O s a m u . . . 1 0 1 , 1 9 6 G e r t n e r , A b i g a i l S . . . 125
G o l d b e r g , Eli . . . 215
G o m e z , F e r n a n d o . . . 84
G r i s o l i , F a b r i z i o . . . 174
Giizey, C e m M e d d i n . . . 194
H e a r s t , M a r t i A . . . 78
H i g u c h i , T e t s u y a . . . 101
H i r a k a w a , H i d e k i . . . 207
H o n g , T a o . . . 186
H u l l , J o n a t h a n J . . . 186
H u l l , R i c h a r d . . . 84
I i d a , H i t o s h i . . . 1 0 1 , 1 9 6 I k e h a r a , S a t o r u . . . 184, 190, 198 I n g r i a , R o b e r t . . . 132
I w a y a m a , M a k o t o . . . 162
J a c q u e m i n , C h r i s t i a n . . . 113
K a t o , T s u n e a k i . . . 107
K a t o h , N a o t o . . . 28
K i m , M y u n g h e e . . . 215
K i t t r e d g e , R i c h a r d . . . 215
K i y o n o , M a s a k i . . . 72
K o m a t s u , Y a s u n o r i . . . 198
Korelsky, T a t i a n a . . . 1
K u k i c h , K a r e n . . . 7
K u r u S z , h k e r . . . 144
M c G r a n a g h a n , M a t t h e w . . . 138
M c K e o w n , K a t h l e e n . . . 7
M u r a k i , K a z u n o r i . . . 41
N a k a m u r a , M a r i k o . . . 207
N a k a y a m a , T a k e h i r o . . . 22
N i r e n b u r g , Sergei . . . 95
N o m u r a , K o u i c h i . . . 207
Oflazer, K e m a l . . . 144, 194 O g u r a , K e n t a r o . . . 190
Oi, K o z o . . . 101
O k u , M a s a h i r o . . . 156
O k u m u r a , A k i t o s h i . . . 41
O m i , Yoshie . . . 184
P a l m e r , D a v i d D . . . 78
P a s e r o , R o b e r t . . . 205
P a z i e n z a , M a r i a T e r e s a . . . 174
Polgu~re, A l a i n . . . 215
Pr6sz6ky, G £ b o r . . . 213
R i c h a r d e t , N a t h a l i e . . . 205
R S s n e r , D i e t m a r . . . 209
S a b a t i e r , P a u l . . . 205
S a m m o u d a , E l y , s . . . 188
Sch/iler, R e i n h a r d . . . 192
S e g a m i , C a r l o s . . . 84
S h a w , J a m e s . . . 7
S h i r a i , S a t o s h i . . . 184
S i b u n , P e n e l o p e . . . 15
S p i t z , A. L a w r e n c e . . . 15
Spyns, P e t e r . . . 150
S t a l l a r d , D a v i d . . . 132
S t e d e , M a n f r e d . . . 209
S t r z a l k o w s k i , T o m e k . . . 168
S u m i t a , E i i c h i r o . . . 101
T a p a n a i n e n , P a s i . . . 47
T o k u n a g a , T a k e n o b u . . . 162
T s u j i i , J u n ' i c h i . . . 72
T s u k a h a r a , N o b u y u k i . . . 198
V o u t i l a i n e n , A t r o . . . 47
W a k a o , T a k a h i r o . . . 182
W e b b e r , B o n n i e L . . . 125
W u , D e k a i . . . 180
Yokoo, A k i o . . . 184
Zribi, A d n a n e . . . 188
