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Richard K i t t r e d g e , C h a i r p e r s o n

Universitd de Montreal Montreal, Quebec PQH3C3J7

Panelists

Joan Bachenko, Naval Research L a b o r a t o r y Ralph Grishman, New York University Donald E. Walker, SRI International Ralph Weischedel, University of Delaware

5.1 W h y Are Sublanguages Important for Applied Computational Lingustics?

F o u r of the five panels at this workshop are assess- ing the perspectives in applied computational linguis- tics for four important problem areas: natural-language interfaces, machine translation, text generation, and concept extraction. F o r each of these areas, it is as- sumed that any applied system will be oriented toward the particular variety of natural language associated with a single knowledge domain. This follows from the now widely accepted fact that such systems require rather tight, primarily semantic, constraints to obtain a correct analysis, and that such constraints can at pres- ent be stated only for sublanguages, not for the lan- guage as a whole. Although a practical system may well have c o m p o n e n t s that are designed to accommo- date the whole language, it must also anticipate the particular syntactic, lexical, semantic, and discourse properties of the sublanguage in which it will operate.

R e s e a r c h into the linguistic structure of w e a t h e r reports, medical records, and aircraft m a i n t e n a n c e manuals has led to specialized grammars for the sub- languages of these domains. Central to each sublan- guage grammar is a statement of the functionally simi- lar word classes and the c o - o c c u r r e n c e restrictions among these classes. When a parser, g e n e r a t o r , or translation system incorporates such a precise linguis- tic description, it becomes not only more efficient but also capable of discriminating b e t w e e n sentences (and texts) that are a p p r o p r i a t e to the d o m a i n and those that are grammatical but inappropriate. In addition, the word classes used in the grammar, and the hierar- chies relating these classes, are an important part of the knowledge structure for the domain.

5.2 H o w Do S u b l a n g u a g e s A r i s e ?

When natural language is used in a sufficiently restricted setting, we may be justified in calling the resultant forms a sublanguage. Although there is no generally a c c e p t e d definition of this term. Several

factors are usually present when the subset of a natu- ral language is restricted enough for efficient semantic processing.

• Restricted domain of reference. The set of objects and relations to which the linguistic expressions refer is relatively small.

• Restricted purpose and orientation. The relation- ships among the participants in the linguistic ex- change are of a particular type and the purpose of the exchange is oriented towards certain goals. • R e s t r i c t e d m o d e of c o m m u n i c a t i o n . C o m m u n i c a -

tion m a y be spoken or written, but there are constraints on the form of expression, which may include " b a n d w i d t h " limitations. Compressed (or telegraphic) language forms may reflect the time and space constraints of certain c o m m u n i c a t i o n modes.

• C o m m u n i t y of participants sharing specialized knowledge. The best canonical examples of sub- languages are those for which there exists an iden- tifiable community of users who share specialized knowledge and who communicate under restrictions of domain, purpose, and mode by using the sublan- guage. These participants e n f o r c e the special pat- terns of usage and ensure the c o h e r e n c e and com- pleteness of the sublanguage as a linguistic system.

5.3 Constraints and Extensions in the Grammar of a Sublanguage

A typical sublanguage makes use of only a part of the language's lexical, morphological, syntactic, seman- tic, and discourse structures. These restrictions on its grammar, once d e t e c t e d and e n c o d e d in the form of rules, can be exploited during automatic processing by greatly reducing the n u m b e r of possibilities to be con- sidered. A sublanguage may also exhibit structures (and, hence, rules) that are not normally regarded as part of the standard language. In the most general case, then, a sublanguage g r a m m a r intersects, but is not contained in, the grammar of the general or stand- ard language from which it derives.

Some of the typical constraints and extensions found in each c o m p o n e n t of a sublanguage grammar are given below, along with r e f e r e n c e to r e c o g n i z e d techniques for describing the constraints and for iden- tifying them in a corpus of texts, when appropriate. In

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Richard Kittredge Sublanguages

addition, we m e n t i o n a n u m b e r of m e c h a n i s m s f o r capturing these constraints for the p u r p o s e s of c o m - puter processing.

5.3.1 Lexical and Morphological Characteristics T h e most o b v i o u s f e a t u r e of a sublanguage is its specialized lexicon. N o t only is the set of w o r d f o r m s (and their possible meanings) highly restricted, but the productive w o r d - f o r m a t i o n rules m a y be of a particular kind, s o m e t i m e s unique to the s u b l a n g u a g e or to a family of related sublanguages. Texts in medicine and p h a r m a c o l o g y , for example, m a y contain a rich v a r i e t y of n a m e s for diseases and drugs, which are c o n s t r u c t e d using c h a r a c t e r i s t i c affixes. Military s u b l a n g u a g e s m a k e f r e q u e n t use of a c r o n y m s which o b e y describa- ble rules of n o u n p h r a s e f o r m a t i o n in the g r a m m a r . M a n y sublanguages e m p l o y symbolic expressions (e.g., m a t h e m a t i c s ) or a b b r e v i a t i o n s which can be shown to have their o w n m o r p h o l o g i c a l characteristics.

Techniques for identifying the special m o r p h o l o g y of s u b l a n g u a g e t e r m s are readily available f r o m lin- guistics. In cases where the lexicon is large, the de- signer of a c o m p u t a t i o n a l s y s t e m m a y find it profitable to include w o r d - f o r m a t i o n rules in a special processing phase.

5.3.2 Syntactic Characteristics

Early w o r k on restricted language has s h o w n that the syntactic description of a naturally occurring sub- language m a y differ significantly f r o m t h a t of a unrestricted language. In the highly c o n s t r a i n e d style of w e a t h e r bulletins, there is little r e s e m b l a n c e b e - tween the syntactic structure of telegraphic f o r e c a s t s and that of general language. T h e syntactic rules are essentially those of a s e m a n t i c g r a m m a r ( B u r t o n 1976). T h e TAUM-METEO system ( C h e v a l i e r et al. 1978) f o r t r a n s l a t i n g C a n a d i a n w e a t h e r bulletins is based on a g r a m m a r arrived at through a distributional analysis of a large corpus of these texts. In less ster- e o t y p e d sublanguages such as medical records, there m a y be b o t h elliptical s e n t e n c e f o r m s and their full- s e n t e n c e p a r a p h r a s e s in the s u b l a n g u a g e . T h u s the NYU s y s t e m for extracting f o r m a t t e d data f r o m medi- cal r e c o r d s (Sager 1978, 1981) m u s t include in its parser special rules for elliptical f o r m s as well as m o r e general syntactic rules for the full forms.

M o s t sublanguages of English o b s e r v e the syntactic p a t t e r n s of standard English but m a y differ m a r k e d l y in the f r e q u e n c y of usage of various c o n s t r u c t i o n s . F o r e x a m p l e , m a n y of the q u e s t i o n f o r m s , stylistic inversions, and exclamatives of c o n v e r s a t i o n a l English are totally absent f r o m technical literature ( L e h r b e r g e r 1981). G r a m m a r s for processing technical language m a y t h e r e f o r e delete the c o r r e s p o n d i n g p r o d u c t i o n rules for analysis in technical domains. O n the o t h e r hand, s o m e sublanguages m a y use syntactic construc-

tions u n k n o w n in the general language, in which case the a p p r o p r i a t e p r o d u c t i o n s m u s t be included in the sublanguage g r a m m a r .

E v e n w h e n certain g r a m m a t i c a l constructions can- not be ruled out of the g r a m m a r , they m a y be of such high or low f r e q u e n c y in the s u b l a n g u a g e t h a t this fact can be used to reorganize the o r d e r in which rules are tried or to change the p r e f e r e n c e weighting assigned to c o m p e t i n g syntactic analyses.

5.3.3 S e m a n t i c C o n s t r a i n t s

T h e r e s t r i c t e d d o m a i n of r e f e r e n c e of a s u b l a n - guage is m i r r o r e d in the w a y words are used with re- spect to o n e a n o t h e r . A d i s t r i b u t i o n a l analysis of w o r d c o - o c c u r r e n c e s in a large corpus of texts ( H a r r i s 1963; H i r s c h m a n , G r i s h m a n , and Sager 1975) allows a c o m p u t a t i o n a l linguist to group words into equivalence classes and to d e s c r i b e the o c c u r r i n g s e n t e n c e s in t e r m s of these classes. C o m p u t a t i o n a l s y s t e m s which use the s e m a n t i c g r a m m a r a p p r o a c h ( B u r t o n 1976) state the syntax directly in t e r m s of such distributional classes, which are r e l e v a n t for the s e m a n t i c or func- tional distinctions to which the s y s t e m s sensitive. Collapsing syntax and semantics in this w a y is useful for small sublanguages ( H e n d r i x et al. 1978; E p s t e i n and Walker 1978), but there is the d i s a d v a n t a g e that the g r a m m a r has no generality and a new one has to be w r i t t e n f o r e a c h n e w s u b l a n g u a g e . T h o u g h o n e a r g u m e n t for s e m a n t i c g r a m m a r s has b e e n that they are c o m p u t a t i o n a l l y m o r e efficient, r e c e n t e x p e r i m e n t s in which a s e m a n t i c g r a m m a r was c o m p a r e d with a linguistically m o t i v a t e d g r a m m a r for the s a m e d a t a b a s e d e m o n s t r a t e d that the latter could be just as efficient

(cf. Sagalowicz 1980).

In m o r e c o m p l e x sublanguages it is usually neces- sary to m a i n t a i n t r a d i t i o n a l s y n t a c t i c c a t e g o r i e s , a n d hence to couch parsing rules in t e r m s of these c a t e g o r - ies. In this case, s e m a n t i c c o n s t r a i n t s in the f o r m of selectional restrictions can be applied either during or directly a f t e r parsing to eliminate those syntactic a n a - lyses that give m e a n i n g s impossible in the s u b l a n g u a g e (Sager a n d G r i s h m a n 1975, Sager 1981, R o b i n s o n 1,980).

M o s t sublanguage texts also h a v e larger i n f o r m a - tion structures b e y o n d the word-class c o - o c c u r r e n c e s of single sentences. An analysis of the i n f o r m a t i o n f o r m a t s of m e d i c a l r e c o r d s ( H i r s c h m a n a n d Sager 1981) has b e e n carried out for the p u r p o s e of infor- m a t i o n retrieval. F r a m e - l i k e structures m a y also be e m p l o y e d to recognize and e x t r a c t larger i n f o r m a t i o n c o m p o n e n t s (e.g., B o b r o w et al. 1977, Schank et al. 1980).

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entails the a s s i g n m e n t of p r o p o s i t i o n a l s t r u c t u r e s to text passages ( W a l k e r and H o b b s 1981). D o m a i n and p r o t o c o l analysis (Davis 1977, Newell a n d Simon 1972, M a l h o t r a 1975) provide techniques for h y p o t h - esizing facts and i n f e r e n c e rules a p p r o p r i a t e for se- mantic analysis and reasoning procedures. K n o w l e d g e acquisition p r o c e d u r e s (Davis 1977, H a a s and H e n d r i x 1980, R y c h e n e r 1980), n o w under investigation, could significantly aid in the building of semantic and infer- ence c o m p o n e n t s .

5.3.4 D i s c o u r s e C o n s i d e r a t i o n s

R e c e n t research has s h o w n that the w a y in which s e n t e n c e s are strung t o g e t h e r to f o r m c o h e r e n t text can vary considerably f r o m one sublanguage to anoth- er. In addition to differences in discourse-level se- m a n t i c s t r u c t u r e s (see 5.3.3), s e p a r a t e s u b l a n g u a g e s m a y m a k e d i f f e r e n t use of a l a n g u a g e ' s linguistic m e a n s of textual cohesion. In view of the considera- ble a t t e n t i o n given to a n a p h o r a in the literature of c o m p u t a t i o n a l linguistics, it is worthwhile to note that certain technical sublanguages contain no o c c u r r e n c e s of anaphoric pronouns, while others m a k e use of spe- cial anaphoric devices (Kittredge 1981). E v e n w h e n a technical s u b l a n g u a g e uses p r o n o m i n a l a n a p h o r a , it often a p p e a r s that the sublanguage effectively restricts it to cases where the a n t e c e d e n t noun phrase occurs in the preceding sentence or even in an earlier clause in the same sentence. Needless to say, the s t r a t e g y e m - ployed for establishing c o - r e f e r e n c e in a sublanguage must therefore take into a c c o u n t the b e h a v i o r of each a n a p h o r i c device in that same sublanguage. In m a n y cases, a far simpler algorithm can be used t h a n would be necessary for unrestricted language. In a n y given language, the s e m a n t i c c o h e r e n c e and g r a m m a t i c a l c o h e s i o n of a text can be signalled b y a v a r i e t y of linking devices. F r o m a language's i n v e n t o r y of de- vices, each sublanguage seems to m a k e a r a t h e r dis- tinctive and limited selection. Stock m a r k e t r e p o r t s avoid repetition of the same v e r b in successive sen- tences, using s y n o n y m s instead, w h e r e a s technical manuals a p p a r e n t l y avoid s y n o n y m y at the e x p e n s e of lexical repetition (Kittredge 1981). T h e use of tense or tense v a r i a t i o n m a y also fit a distinctive p a t t e r n . All such tendencies, w h e t h e r probabilistic or absolute, m a y be exploited during the design of o p t i m i z e d sub- language processing systems.

5.4 Factors Defining S u i t a b l e C a n d i d a t e A p p l i c a t i o n s

The sublanguage a p p r o a c h to language processing m a y not be a p p r o p r i a t e to all varieties of restricted language or all types of application. It m a y only be profitable where there exists an established group of users who help to identify and define the knowledge domain. In addition, the domain should be relatively well-defined and internally consistent. The m o s t tract-

able s u b l a n g u a g e s f r o m the c o m p u t a t i o n a l point of view are those that p r e s e n t a simple discourse struc- ture. Finally, each application should be one in which the c o m p u t e r is an a p p r o p r i a t e m e d i u m of c o m m u n i c a - tion or processing (e.g., s p o k e n sublanguages or ones for which p e r m a n e n t records would not or should not be kept m a y not be a p p r o p r i a t e ) .

In practical applications where e c o n o m i c considera- tions are decisive, one must also take into a c c o u n t the time and cost of studying the linguistic properties in a sufficiently large and r e p r e s e n t a t i v e s a m p l e of the s u b l a n g u a g e and of c r e a t i n g a n d p r o g r a m m i n g the s u b l a n g u a g e - s p e c i f i c d i c t i o n a r y and g r a m m a r rules. T h e r e is r e a s o n to believe that sublanguages that are s e m a n t i c a l l y and p r a g m a t i c a l l y n e a r - n e i g h b o r s are similar in their g r a m m a t i c a l properties, so that a b e t t e r u n d e r s t a n d i n g of language f o r m and f u n c t i o n will m a k e the description of new sublanguages easier and m o r e predictable.

5.5 M a t u r i n g Areas of Research R e l e v a n t to t h e S u b l a n g u a g e A p p r o a c h

A successful general a p p r o a c h to sublanguage proc- essing in a wide v a r i e t y of d o m a i n s will d e p e n d on a d v a n c e s in a n u m b e r of research areas, some of which are maturing rapidly. Empirical w o r k on k n o w l e d g e structures ( B o b r o w et al. 1977, M a r k 1980, R o b i n s o n et al. 1980) and on m e c h a n i s m s of focus ( G r o s z 1977, 1981) is relevant to a p r o p e r t r e a t m e n t of sublanguage specific features of discourse and semantic structure.

Techniques of using precise selectional restrictions f o r s u b l a n g u a g e s h a v e b e e n i m p l e m e n t e d ( B u r t o n 1976) as have those for extracting f o r m a t t e d i n f o r m a - tion f r o m fairly s t e r e o t y p e d s u b l a n g u a g e s (Sager 1978). A new technique for developing t r a n s p o r t a b l e s y s t e m s for n a t u r a l - l a n g u a g e i n t e r f a c e s to d a t a b a s e s ( H e n d r i x and Lewis 1981) elicits f r o m the user a lan- guage for querying the c o n t e n t s at the same time that i n f o r m a t i o n a b o u t the domain is being entered. This a p p r o a c h is being e x t e n d e d to provide a m o r e sophisti- cated s y s t e m that is not limited to f o r m a t t e d d a t a b a s e s but entails translation into a set of w e l l - f o r m e d f o r m u - las in a m a n y - s o r t e d f i r s t - o r d e r logic ( H a a s and H e n - drix 1980). R e c e n t w o r k on treating d e p a r t u r e s f r o m g r a m m a t i c a l i t y ( S o n d h e i m e r and W e i s c h e d e l 1980, H a y e s and M o u r a d i a n 1980, M c K e o w n 1980, K w a s n y and S o n d h e i m e r 1981, Miller et al. 1981) can be use in handling specialized language that deviates syntacti- cally f r o m the s t a n d a r d language. Devices for design- ing m o r e " f r i e n d l y " s y s t e m s , such as the w o r k on graceful interaction ( K a p l a n 1978, H a y e s and R e d d y 1979, Weischedel and S o n d h e i m e r 1981) are relevant to the question of relating sublanguage-specific p h e - n o m e n a to those of the whole language.

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Richard Kittredge Sublanguages

5.6 P r o m i s i n g N e w R e s e a r c h A r e a s

A n u m b e r of new or e v e n u n d e r d e v e l o p e d research areas will certainly p r o v e i m p o r t a n t for w o r k on sub- language. We expect that further research on s y n t a c - tic variation will yield a m o r e unified f r a m e w o r k for the description of sublanguage word and phrase struc- ture. W o r k in pragmatics, such as the recent c o m p u t a - tional modeling of speech acts, will intersect with in- v e s t i g a t i o n s into s u b l a n g u a g e s w h e r e social or legal dimensions are important. As we a c c u m u l a t e experi- ence in s e m a n t i c processing o v e r a n u m b e r of specialty areas, we will be able to identify m o r e a n d m o r e sharply the i m p o r t a n t p a r a m e t e r s f o r assessing the c o m p u t a t i o n a l t r a c t a b i l i t y of a n y given s u b l a n g u a g e . This experience will also nourish a distinct area which has b o t h theoretical and practical aspects: the p r o b - lem of relating sublanguages ( a n d their g r a m m a r s ) to the standard language (and its g r a m m a r ) . T h e pre- liminary efforts at building up a t a x o n o m y and t y p o l o - gy of sublanguages are aimed in this direction.

T h e r e is already an identifiable m o v e m e n t t o w a r d s codifying and teaching language f o r specific purposes. F o r some applications it is possible to take naturally occurring sublanguages and slightly regularize t h e m so that strong tendencies are p r o m o t e d to n o r m s for c o m - municating in the subfield. A t t e m p t s in this direction have o c c u r r e d in the stylistic guidelines n o w used for writing w e a t h e r r e p o r t s and aircraft m a i n t e n a n c e m a n - uals. A serious scientific a p p r o a c h to this " e n g i - n e e r i n g d e s i g n " of n e w s u b l a n g u a g e s m u s t await a m o r e exact theoretical and practical u n d e r s t a n d i n g of h o w language function relates to language form.

5.7 R e c o m m e n d a t i o n s

At present, only a small n u m b e r of sublanguages haw~ b e e n studied in detail. Thus o n e urgent need is to b r o a d e n the basis of o u r u n d e r s t a n d i n g of these linguistic subsystems. T h e m e m b e r s of the panel feel tlhat this can best be achieved b y selecting a f e w p r o m - i,dng a p p l i c a t i o n areas in which to c o n c e n t r a t e s u b - s t a n t i v e r e s e a r c h resources. Such c o n c e n t r a t i o n is n e c e s s a r y f o r several reasons. First, m o s t naturally o c c u r r i n g s u b l a n g u a g e s p r e s e n t real challenges f o r linguistic description. M a n y m o n t h s or years of e f f o r t m u s t usually be i n v e s t e d in d e s c r i b i n g a c o r p u s of texts and in finding the natural extensions of t h a t cor- pus in c o l l a b o r a t i o n with s p e a k e r s of the sublanguage. Second, the linguistic peculiarities of the s u b l a n g u a g e o f t e n p r e s e n t new p r o b l e m s f o r c o m p u t a t i o n a l t r e a t - m e n t , particularly if the solutions are to be generaliza- ble to other, related sublanguages. Third, m a n y fur- ther m o n t h s of on-site testing are usually n e c e s s a r y to p r o p e r l y a b s o r b and e v a l u a t e the f e e d b a c k f r o m users of p r o t o t y p e s y s t e m s , and to e v o l v e m o r e a d e q u a t e versions. T h e evolution of a n y significant new s y s t e m t h e r e f o r e implies a substantial collaborative e f f o r t o v e r a period ranging f r o m several m o n t h s to several years.

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6. A c k n o w l e d g e m e n t s

T h i s w o r k s h o p is t h e f i r s t in a s e r i e s o r g a n i z e d b y t h e N a v y C e n t e r f o r A p p l i e d R e s e a r c h in A r t i f i c i a l I n t e l l i g e n c e . T h e c o n c e p t f o r this w o r k s h o p e m e r g e d f r o m n u m e r o u s d i s c u s s i o n s w i t h M a r v i n D e n i c o f f a n d J o e l T r i r n b l e o f O N R , P a u l C h a p i n a n d H e n r y H a m - b u r g e r o f NSF, R o b e r t E n g e l m o r e a n d R o b e r t K a h n o f D A R P A , S t a n l e y W i l s o n a n d J o h n D a v i s o f NRL, a n d W i l l i a m P r i c e o f A F O S R .

T h e w o r k s h o p i t s e l f w a s m a d e p o s s i b l e o n l y t h r o u g h t h e s u p e r b c o o p e r a t i o n o f t h e A C L . N o r m S o n d h e i m e r , f o r m e r A C L p r e s i d e n t , a n d D o n W a l k e r , A C L S e c r e t a r y - T r e a s u r e r , u s e d t h e i r o r g a n i z a t i o n a l t a l e n t s to i n c o r p o r a t e t h e w o r k s h o p i n t o t h e 1981 A C L C o n f e r e n c e . J e r r y K a p l a n , l o c a l c h a i r m a n f o r t h e A C L m e e t i n g , g r a c i o u s l y a c c e p t e d t h e a d d e d r e s p o n s i b i l i t y o f p r o v i d i n g l o c a l a r r a n g e m e n t s f o r t h e w o r k s h o p .

W e g r a t e f u l l y a c k n o w l e d g e t h e v e r y c o m p e t e n t s e c r e t a r i a l a s s i s t a n c e b y J a n e t L. S t r o u p o f N R L a n d t h e c a r e f u l c o m p i l a t i o n o f t h e w o r k s h o p p r o c e e d i n g s b y V e r o n i c a B a t e s o f NRL. F i n a n c i a l s u p p o r t f o r t h e w o r k s h o p w a s p r o v i d e d b y t h e O f f i c e o f N a v a l R e - s e a r c h .

R e f e r e n c e s

Artificial Intelligence Corporation 1 9 8 1 Intellect Query System User's Guide. Release 101. Artificial Intelligence Corp., Walt- ham, MA.

Bicrmann, A. and Ballard, B. 1980 Toward Natural Language Computation, AJCL 6 No. 2, 71-86.

Bobrow, R. 1 9 7 8 The R U S System. BBN report 3878. Bolt, Beranek, and Newman, Inc., Cambridge, MA.

Bobrow, D., Kaplan, R., Kay, M., Norman, D., Thompson, H., and Winograd, T. 1 9 7 7 GUS, A Frame-Driven Dialogue System.

Artificial Intelligence 8 155-173.

Brown, J., Burton, R., and Bell, S. 1974 SOPHIE: A Sophisticated Instructional Environment for Teaching Electronic Troubleshooting.

BBN Report 2790 (March).

Burton, R. 1976 Semantic Grammar: An Engineering Technique for Constructing Natural Language Understanding Systems. BBN Report 3453, Bolt, Beranek, and Newman, Inc. Cambridge, MA (December).

Carbonell, J. and Hayes, P. 1 9 8 1 Dynamic Strategy Section in Flexible Parsing. Nineteenth Annual Meeting of the Association for Computational Linguistics. Stanford, CA (June).

Chevalier, L., Dansereau, J., and Poulin, G. 1978 TAUM-METEO: Description du Syst~me. Universite de Montreal, Canada. Codd, E. 1974 Seven Steps to Rendezvous with the Casual User.

In Klimbie, J. and Koffeman, K., Eds., Data Base Management.

North-Holland, Amsterdam: 179-200.

Codd, E. 1 9 7 8 How About Recently? (English Dialogue with Relational Databases Using RENDEZVOUS Version 1). In Shneiderman, B., Ed., Databases: Improving Usability and Responsiveness. Academic Press, New York: 3-28.

Davis, R. 1 9 7 7 Interactive Transfer of Expertise: Acquisition of New Inference Rules. In Proceedings of the Fifth International Conference on Artificial Intelligence. Cambridge, MA: 321-328. Epstein, M. and Walker, D. 1978 Natural Language Access to a

Melanoma Data Base. In Proceedings of the Second Annual Symposium on Computer Application in Medical Care. IEEE, New York: 320-325.

Grishman, R, and Hirschman, L. 1978 Question Answering from Natural Language Data Bases. Artificial Intelligence 25-43. Grosz, B. 1 9 8 1 Focusing and Description in Natural Language

Dialogues. In Joshi, A., Sag, I., and Webber, B., Eds., Elements of Discourse Understanding: Proceedings of a Workshop on Compu- tational Aspects of Linguistic Structure and Discourse Setting.

Cambridge University Press, Cambridge: 84-105.

Grosz, B. 1977 The Representation and Use of Focus in a System for Understanding Dialogs. Proceedings of the Fifth International Joint Conference on Artificial Intelligence. Cambridge, MA

(August 22-25): 67-76.

Haas, N. and Hendrix, G. 1980 An Approach to Acquiring and Applying Knowledge. In Proceedings of the First Annual Nation- al Conference on Artificial Intelligence. Stanford University: 235-239.

Hendrix, G. and Lewis, W. 1981 Transportable Natural-Language Interfaces to Databases. In Proceedings of the Nineteenth Annu- al Meeting of the Association for Computational Linguistics. Stan- ford, CA (June).

Hendrix, G., Sacerdoti, E., Sagalowicz, D. and Slocum, J. 1978 Developing a Natural Language Interface to Complex Data.

A C M Transactions on Database Systems 3 No. 2 (June) 105-147. Harris, Z. 1963 Discourse Analysis Reprints. The Hague, Mouton. Hayes, P. and Mouradian, G. 1980 Flexible Parsing. In Proceed-

ings of of the lSth Annual Meeting of the Association for Compu- tational Linguistics. University of Pennsylvania: 97-103. Hayes, P. and Reddy, R. 1979 Graceful Interaction in Man-

Machine Communication. Sixth International Joint Conference on Artificial Intelligence. Stanford University, 372-374.

Hirschman, L., Grishman, R., and Sager, N. 1975 Grammatically- Based Automatic Word Class Formation. Information Process- ing and Management 11.

Hirschman, L. and Sager, N. 1981 Automatic Informatting of a Medical Sublanguage. In Kittredge and Lehrberger.

Joshi, A., Mays, E., Lanka, S., and Webber, B, 1 9 8 1 Natural Language Interaction with Dynamic Knowledge Bases: Monitors as Responses. In Proceedings of the IJCAI 1981. Vancouver, Vancouver (August).

Kameny, I. et al. 1978 An End User Friendly Interface for Data- bases. Proceedings VLDB. Berlin.

Kaplan, S.J. 1979 Cooperative Responses from a Portable Language Data Base Query System. Ph.D. Dissertation, University of Penn- sylvania. (Available as Stanford Heuristic Programming Project Report HPP-79- 19, Computer Science Department, Stanford University, Stanford, CA, 94305 (July).)

Kaplan, S.J. 1978 Indirect Responses to Loaded Questions. Theo- retical Issues in Natural Language Processing-2. University of Illinois at Urbana-Champaign (July).

Kaplan, S.J. and Davidson, J. 1981 Interpreting Natural Language Database Updates. In Proceedings of the Nineteenth Annual Meeting of the Association for Computational Linguistics. Stan- ford, CA, June.

Kaner, R. and Montgomery, C. 1972 On-Line Bugging: Hope for Terminal Cases of Semantic Deviance. Invited Paper at the Gordon Research Conference on the Frontiers of Science. New London, NH, July.

Kay, M. 1979 Functional Grammar. In Proceedings of the Fifth Annual Meeting of the Berkeley Linguistics Society.

Kittredge, R. 1981 Variation and Homogeneity of Sublanguages. In Kittredge and Lehrberger.

Kittredge, R. and Lehrberger, J. Eds. 1981 Sublanguage: Studies of Language in Restricted Semantic Domains. deGruyter, Berlin. Kwasny, S. and Sondheimer, N. 1 9 8 1 Ungrammaticality and

Extragrammaticality in Natural Language Understanding Sys- tems. In Proceedings of the Seventeenth Annual Meeting of the ACL. La Julia, CA (August).

(6)

Carroll Johnson and Joan Bachenko Proceedings of the Workshop

Landsbergen, S. and Scha, R. 1978 Formal Languages for Seman- tic Representation. In Petofi, J., Ed., Aspects o f Automated Text Processing. Buske, Hamburg.

Lehrberger, J. 1981 Automatic Translation and the Concept of Sublanguage. In Kittredge and Lehrberger.

Mckeown, K. 1980 Generating Relevant Explanations: Natural Language Responses to Questions About Database Structure. In Proceedings o f First Meeting o f AAAI. Stanford, CA (August).

Malhotra, A. 1975 Design Criteria for a Knowledge-Based English Language System for Management: An Experimental Analysis. MAC TR 146. Cambridge, MA: Project MAC. Massachusetts Institute of Technology, February.

Mark, W. 1980 Rule-Based Inference in Large Knowledge Bases. In Proceedings o f the First Annual National Conference on Artifi- cial Intelligence. Stanford, CA.

Mays, E. 1980 Failures in Natural Language Systems: Applica- tions to Database Query Systems. In Proceedings o f the First Meeting o f AAAI. Stanford, CA, August.

Miller, L., Heidorn, G., and Jensen, K. 1981 Text-critiquing with the EPISTLE System: An Author's Aid to Better Syntax. In

A F I P S Conference Proceedings. AFIPS Press, Montvale, NJ: 649-655.

Moore, R.C. 1 9 8 1 Problems in Logical Form. In Proceedings o f the Nineteenth Annual Meeting o f the A C L (June).

Newell, A. and Simon, H. 1972 Human Problem Solving. Prentice- Hall, Englewood Cliffs, NJ.

Novak, G.S., Jr. 1981 Physics Problem Solving: ISAAC-II. In

Proceedings o f the Seventh International Joint Conference on Arti- ficial Intelligence. IJCAI-81, Vol. 2. University of British Co-

lumbia, Vancouver, B.C. (August).

Petrick, S. 1975 Design of the Underlying Structure for a Data Base Retrieval System. In Grishman, R., Ed., Directions in Artificial Intelligence: Natural Language Processing. Courant Computer Science Report 7, Courant Institute of Mathematical Sciences, York University, New York, New NY, 60-93.

Robinson, A., Appelt, D., Grosz, G., Hendrix, G., and Robinson, J. 1980 Interpreting Natural Language Utterances in Dialog about Tasks. Communications o f the A C M in press. SRI Tech- nical Note 210. Artificial Intelligence Center, SRI Internation- al, Menlo Park, CA.

Robinson, J. 1982 DIAGRAM: A Grammar for Dialogues. Com- munications o f the A CM.

Rychener, M. 1980 Approaches to Knowledge Acquisition: The lnstructable Production System Project. In Proceedings o f the First Annual Conference on Artificial Intelligence. Stanford, CA: 228-230.

Sagalowicz, D., Ed. 1980 Mechanical Intelligence: Research and Applications. Final Technical Report. Artificial Intelligence Center, SRI International. Menlo Park, CA.

',~agcr, N. 1981 Natural Language Information Processing: A Com- puter Grammar o f English and Its Applications. Addison-Wesley, Reading, MA.

'Sager, N. 1978 Natural Language Information Formatting: The Automatic Conversion of Texts to a Structure Data Base. In Yovits, M. and Rubinoff, M., Eds., Advances in Computers.

Academic Press, New York: 89-162.

Sager, N. and Grishman, R. 1975 The Restriction Language for Computer Grammars. Communications o f the A C M 18 390-400. Schank, R., Lebowitz, M. and Birnbaum, L. 1980 An Integrated

Understander. American Journal o f Computational Linguistics 6

13-30.

Silva, G.M.T., Dwiggins, D.L., Busby, S.G., and Kuhns, J.L. 1979

A Knowledge-Based Automated Message Understanding Methodolo- gy for an Advanced Indications System. OSI Report R79-006, Operating Systems, Inc. (February).

Simmons, R. F. and Chester, D. Relating Sentences and Semantic Networks with Clausal Logic. Communications o f the ACM, to appear.

Sondheimer, N. and Weischedel, R. 1980 A Rule-Based Approach to 111- Formed Input. In Proceedings o f the Eighth International Conference on Computational Linguistics: 46-53.

Thompson, F. and Thompson, B. 1975 Practical Natural Language Processing: The REL System as Prototype. In Rubinoff, M. and Yovits, M.C., Eds., Advances in Computers, Volume 13.

Academic Press, New York.

Walker, D. and Hobbs, J. 1981 Natural Language Access to Medical Text. In Proceedings o f the Fifth Annual Symposium on Computer Applications in Medical Care. IEEE, New York. Waltz, D.L. 1978 An English Language Question Answering

System for a Large Relational Data Base. Communications o f the A C M 21 526-539.

Weischedel, R. and Black, J. 1979 Responding to Potentially Un- parsable Sentences. Tech Rep. 79/3. Department of Computer and Information Sciences, Universiy of Delaware, Newark, DE.

Weischedel, R. and Sondheimer, N. 1981 A Framework for Proc- essing Ill-Formed Input. Technical Report. Department of Com- puter and Information Sciences, University of Delaware, New- ark, DE.

References

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