Discourse Pragmatics and Ellipsis Resolution 
in Task-Oriented Natural Language Interfaces 
Jaime G. Carbonell 
Computer Science Department 
Carnegie-Mellon University. 
P!ttsburgh, PA 15213 
Abstract 
This paper reviews discourse phenomena that occur frequently 
in task.oriented man.machine dialogs, reporting on a~n empirical 
study that demonstrates the necessity of handling ellipsis, 
anaphora, extragrammaticality, inter-sentential metalanguage, 
and other abbreviatory devices in order to achieve convivial user 
interaction. Invariably, users prefer to generate terse or 
fragmentary utterances instead of longer, more complete "stand- 
alone" expressions, even when given clear instructions tO the 
contrary. The XCALIBUR exbert system interface is designed to 
meet these needs, including generalized ellipsis resolution by 
means of a rule-based caseframe method superior tO previous 
semantic grammar approaches. 
1. A Summary of Task-Oriented Discourse Phenomena 
Natural language discourse exhibits several intriguing 
phenomena that defy definitive linguistic analysis and general 
computational solutions. However, some progress has been 
made in developing tractable computational solutions to 
simplified version of phenomena such as ellipsis and anaphora 
resolution \[20, 10, 211. This paper reviews discourse phenomena 
that arise ~n task.oriented dialogs with responsive agents (such 
as expert systems, rather than purely passive data base query 
systems), outlines the results of an empirical study, and presents 
our method for handling generalized ellipsis resolution in the 
XCALIBUR expert system interface. With the exception of inter- 
sentential metalanguage, and to a lesser degree 
extragrammaticality, the significance of the phenomena listed 
below have long been recognized and documented in the 
computational linguistics literature. 
• Anaphora -- Interactive task-oriented dialogs invite the 
use of anaphora, much more so than simpler data base 
query situations. 
• Definite noun phrases -- As Grosz \[6\] noted, resolving 
the referent of defimte noun phrases requires an 
understanding of the planning structure underlying 
cooperative discourse, 
• Ellipsis -. Sentential level ellipsis has long been 
recognized as ubiquitous in discourse. However, semantic 
ellipsis, where ellipsed information is manifest not as 
syntactically incomplete structures, but as semantically 
incomplete propositions, is also an important 
phenomenon. The ellipsis resolution method presented 
later in this paper addresses both kinds of ellipsis. 
• Extragrammatical utterances -- Interjections, dropped 
articles, false starts, misspellings, and other forms of 
grammatical deviance abound in our data (as explained in 
the following section). Developing robust parsing 
techniques that tolerate errors has been the focus of our 
earlier investigations \[2, 9. 7\] and remains high among our 
priorities. Other investigations on error-tolerant parsing 
incJude \[13, 22\]. 
• Meta.lincjuistic utterances -- Intra-sentential 
metalanguage has been investigated to some degree 
\[18, 12J, but its more common inter-sententiai counterpart 
has received little attention \[4}. However, utterances about 
other utterances (e,g,, corrections of previous commands, 
such as "1 meant to type X instead" or "1 should have said 
...") are not infrequent in our dialogs, and we are making 
an initial stab at this problem \[8}. Note that it is a 
cognitively less demanding task for a user to correct a 
previous utterance than to repeat an explicit sequence of 
commands (or worse yet, to detect and undo explicitly 
each and every unwanted consequence of a mistaken 
command). 
• indirect speech acts -- Occasionally users will resort tO 
indirect speech acts\[19. 16, 1\], especially in connection 
with inter.sentential metalanguage or by stating a desired 
state of affairs and expecting the system tO supply the 
sequence of actions necessary to achieve that state. 
In our prior work we have focused on extr~grammaticality and 
inter.sentential metalanguage. In this paper we report on an 
empLrical study of discourse phenomena to a s~mulated interface 
and on our work on generalized elhpsis resolutLon in the context 
of the XCALIBUR project, 
2. An Empirical Study 
The necessity to handle most of the discourse phenomena 
listed in the preceding section was underscored by an empirical 
study we conducted to ascertain the most pressing needs of 
natural language interfaces in interactive apl~lications, The initial 
objective of this study was to circumscribe the natural language 
interface task by attempting to instruct users of a simulated 
interface not to employ different discourse devices or difficult 
linguistic constructs. In essence, we wanted to determine 
whether untrained users would be able to interact as instructed 
(for instance avoiding all anaphoric referents), and, if so, whether 
they would still find the interface convivial given our artificial 
constraints. 
The basic experimental set-up consisted of two remotely 
located terminals linked to each other and a transaction log file 
164 
that kept a record of all interactions. The user wassituated at one 
terminal and was told he or she was communicating with a real 
natural language interface to an operating system (and an 
accompanying intelligent help system, not unlike Wilensky's Unix 
Consultant\[23\].) The experimenter at the other terminal 
simulated the interface and gave appropriate commands to the 
(real) operating system. 
In different sessions, users were instructed not to use 
pronouns, to type only complete sentences, to avoid complex 
syntax, to type only direct commands or queries (e.g., no indirect 
speech acts or discourse-level metalinguistic utterances \[4, 8\]), 
and to stick to the topic. The only instructions that were reliably 
followed were sticking to the topic (always) and avoiding 
complex syntax (usually). All other instructions were repeatedly 
violated in spite of constant negative feedback -- that is, the 
person pretending to be the natural language program replied 
with a standard error message. I recorded some verbal 
responses as well (with users telling a secretary at the terminal 
what she should type), and, contrary to my expectations, these 
did not qualitatively differ from the typed utterances. The 
significant result here is that users appear incapable or unwilling 
to generate lengthy commands, queries or statements when they 
can employ a linguistic device to state the same proposition in a 
more terse manner. To restate the principle more succinctly: 
Terseness principle: users insist on being as terse 
as possible, independent Of communication media or 
typing ability. 1 
Given these results, we concluded that it was more appropriate 
to focus our investigations on handling abbreviatory discourse 
devices, rather than to address the issue of expanding our 
syntactic coverage to handle verbose complex structures seldom 
observed in our experience. In this manner, the objectives of the 
XCALIBUR project differ from those of most current 
investigations. 
3. A Sketch of the ×CALIBUR interface 
This section outlines the XCALIBUR project, whose objective is 
to provide flexible natural language access (comprehension and 
generation) to the XSEL expert system \[15\]. XSEL, the Digital 
Equipment Corporation's automated salesman's assistant, 
advises on selection of appropriate VAX components and 
produces a sales order for automatic configuration by the R1 
system \[14\]. Part of the XSEL task is to provide the user with 
information about DEC components, hence subsuming the data- 
base query task. However, unlike a pure data base query system, 
an expert system interface must also interpret cnm"'~ndS, 
understand assertions of new information, and carry out task- 
oriented dialogs (such as those discussed by Grosz\[6\]). 
XCALIBUR, in particular, deals with commands to modify an 
order, as well as information requests pertaining to its present 
task or itS data base of VAX component parts. In the near future it 
should process clarificational dialogs when the underlying expert 
system (i.e. XSEL) requires additional information or advice, as 
illustrated in the sample dialog below: 
>What is the largest 11780 fixed disk under $40,000? 
The rp07-aa is a 516 M8 fixed pack disk that costs $38,000. 
>The largest under $50,000? 
The rp07-aa. 
>Add two rpO7-aa disks to my order. 
Line item 1 added: (2 ro07-aa) 
>Add a printer with graphics capatJility 
fixed or changeable font? 
>fixed tont 
lines per minute? 
>make it at least 200, upper/lowercase. 
Ok. Line item 2 added: (1 Ixyt 1-sy) 
>Tell me about the Ixyl 1 
The Ixyl 1 is a 240 I/m line printer with plotting capabilities, 
With the exception of the system-driven clarification 
interchange, which is beyond XCALIBUR's presently 
implemented capabilities, the rest of the dialog, including the 
natural language generation, is indicative of the present state Of 
our system. The major contributions of XCALIBUR thus far is 
perhaps the integratlon of diverse techmques into a working 
system, including the DYPAR.II multi-strategy parser. 
expectatnon.based error correction, case.frame ellipsis 
USER 
-- --~ Oypar.II 
Genet al,.:,r 
\]L~-- 1 InformalLon Manager 
& <_J 
J'(- XSEL 
Long te,m (Static) Database 
XCALIBUR > 
R1 
i 
Figu re 3-1 : Overview of XCALIBUR 
llndicative as these empirical studies are of where one must focus one's 
efforts in developing convivial interfaces, they were not performed with adeqgato 
control groups or statistical rigor. Therefore. there is ample room to confirm. 
refute or expand upon lhe detads of our emoirical findings. However. the 
surprisingly strong form in which Grice's maxgm \[5\] manifests itself in task- 
oa~ented human computer d=alogs seems qualitatively irrefutable. 
resolution and focused natural language generation. Figure 
3.1 provides a simplified view of the major modules of 
XCALIBUR, and the reader is referred to \[3\] for further 
elaboration. 
3.1. The Role of the Information Handler 
When XSEL is ready to accept input, the information handler is 
165 
passed a message indicating the case frame or class of case 
frames expected as a response. For our example, assume that a 
command or query is expected, the parser is notified, and the 
user enters 
>What is the price of the 2/argest dual port fixed media disks? 
The parser returns; 
\[QUERY (OBJECT (SELECT (disk 
(ports (VALUE (2))) 
(disk-pack-type (VALUE (fixed))) 
(OPERATION (SORT 
(TYPE ('descending)) 
(ATTR (size)) 
(NUMBER (2))) 
(PROJECT (price))) 
(INFO-SOURCE ('default)) \] 
Rather than delving into the details of the representation or the 
manner in which it is transformed prior to generating an internal 
command to XSEL, consider some of the functions of the 
information handler: 
• Defaults must be instantiated. In the example, the query 
does not explicitly name an INFO.SOURCE, which could be 
the component database, the current set of line.items, or a 
set of disks brought into focus by the preceding dialog. 
• Ambiguous fillers or attribute names must be resolved. For 
example, in most contexts. "300 MB disk" means a disk 
with "greater than or equal to 300 ME\]" rather than strictly 
"equal to 300 MB", A "large" disk refers to ample memory 
capacity in the context of a functional component 
specification, but to large physical dimensions during site 
planning, Presently, a small amount of local pragmatic 
knowledge suffices for the analysis, but. in the general 
case. closer integration with XSEL may be required. 
• Generalized ellipsis resolution, as presented below, occurs 
within the information handler. 
As the reader may note, the present raison d'etre of the 
information manager ts to act as a repository of task and dialog 
knowledge providing information that the user did not feel 
necessary to convey explicitly. Additionally. the information 
handler routes the parsed command or query to the appropriate 
knowledge source, be it an external static data base, an expert 
system, or a dynamically constructed data structure (such as the 
current VAX order). Our plans call for incorporating a model of 
the user's task and knowledge state that should provide useful 
information to both parser and generator. At first, we intend to 
focus on stereotypical users such as a salesperson, a system 
engineer and a customer, who would have rather different 
domain knowledge, perhaps different vocabulary, and certainly 
different sets of tasks in m,nd. Eventually, refinements and 
updates to a default user model should be inferred from an 
analysis of the current dialog \[17\]. 
4. Generalized Caseframe Ellipsis 
The XCALIBUR system handles ellipsis at the case-frame level. 
Its coverage appears to be a superset of the LIFER/LADDER 
system \[10, 11 \] and the PLANES ellipsis module \[21 \]. Although it 
handles most of the ellipsed utterances we encountered, it is not 
meant to be a general linguistic solution to the ellipsis 
phenomenon. 
4.1. Examples 
The following examples are illustrative of the kind of sentence 
fragments the current case-frame method handles. For brevity, 
assume that each sentence fragment occurs immediately 
following the initial query below. 
INITIAL QUERY: "What is the price of the three largest 
single port fixed media disks?" 
"Speed?" 
"Two smallest?." 
"How about the price of the two smallest" 
"also the smallest with dual ports" 
"Speed with two ports?" 
"Disk with two ports." 
In the representatwe examples above, punctuation is of no help, 
and pure syntax is of very limited utility. For instance, the last 
three phrases are syntactically similar (indeed, the last two are 
indistinguishable), but each requires that a different substitution 
be made on the preceding query. All three substitute the number 
of ports in the original SELECT field, but the first substitutes 
"ascending" for "descending" in the OPERATION field, the 
second subshtutes "speed" for "price" in the I~ROJECT field, and 
the third merely repeats the case header of the SELECT field. 
4.2. The Ellipsis Resolution Method 
Ellipsis ~s resolved differently in the presence or absence of 
strong discourse expectations. In the former case, the discourse 
expectatmon rules are tested first, and, if they fad to resolve the 
sentence fragment, the Contextual substitution rules are tned. If 
there are no strong d~scourse expectations, the contextual 
substitution rules are invoked directly. 
Exemplary discourse expectation rule: 
IF: The system generated a query f,or confirmation or 
dlsconrlrmation of a proposed value of a filler 
of a case in a case frame in Focus, 
THEN: EXPECT one or more of, the f,oIIowing: 
l) A conrirmatlon or disconf,irmation pattern. 
7) A different but semantically permissible f,iller 
of the case frame in questlon (optlonally naming 
the attribute or provlOing the case marker) 
3) A comparatlve or evaluative pattern. 
~) ~ query for posslble rlllers ,)r constralnts on 
possible fillers of the case In question. 
\[If this expectatlon is confirmeo, a sup-dialog 
is entered, wtlere previously Focused entities 
remain in focus. \] 
The following dialog fragment, presented without further 
commentary, ~llustrates how these expectations come into play in 
a focused dialog: 
>Add a line printer with graphics capabilities. 
Is 150 lines per minute acceptable? 
>No. 320 is better Expectations 1, 2 & 3 
(or) other options for the speed? Expectation4 
(or) Too slow. try 300 or faster Expectations 2 & 3 
The utterance "try 300 or faster" is syntactically a complete 
sentence, but semantically ,t is lust as fragmentary as the 
previous utterances. The strong discourse expectations, 
however, suggest that it be processed in the same manner as 
syntactically incomplete utterances, since Jt satisfies the 
expectations of the interactive task The terseness principle 
operates at all levels: syntactic, semantic and pragmatic. 
166 
The contextual substitution rules exploit the semantic 
representation of queries and commands discussed in the 
previous section. The scope of these rules, however, is limited to 
the last user interaction of appropriate type in the dialog focus, 
as ='llustrated in the following example: 
Contextual Substitution Rule 1: 
IF: An attribute name (or conjoined list of" attribute 
names) is present without any corresponding filter 
or case header, and the attribute is a semantically 
permissible descriptor of tile case frame In the 
SELECT rield o9 the last query in focus, 
THEN: Substitute the new attribute name tot the old tiller 
of' the PROJECT field of the last query. 
For example, this rule resolves the ellipsis in the following 
utterances: 
>What is the size of the 3/argest sing/e port fixed media disks? 
>And the price and speed? 
Contextual Substitution Rule 2: 
TF: t~o sentential case frames are recognized tn the 
inpuL, and part of the Input can be recognized as an 
attribute &rtller (or just a riller) of a case In 
the SELECT field or a command or query tn Focus, 
THEN: Substitute t.he new filler for the old in the same 
rteld or the old conlmand or query. 
This rule resolves the following kind of ellipsis: 
>What is the size of the 3 largest single port fixed media disks? 
>disks with two ports? 
Note that it is impossible to resolve this kind of ellipsis in a 
general manner if the previous query is stored verbatim or as a a 
semantic-grammar parse tree. "Disks with two ports" would at 
best correspond to some <disk-descriptor'> non-terminal, 
and hence, according to the LIFER algorithm\[lO, 11\], would 
replace the entire phrase "single port fixed media disks" that 
corresponded to <disk-descriptor> in the parse of the 
original query. However, an informal poll of potential users 
suggests that the preferred interpretation of the ellipsis retains 
the MEDIA specifier of the original query. The ellipsis resolution 
process, therefore, requires a finer grain substation method than 
simply inserting the highest level non-terminals in the in the 
ellipsed input in place of the matching non-terminals in the parse 
tree of the previous utterance. 
Taking advantage of the fact that a case frame analysis of a 
sentence or object description captures the meaningful semantic 
relations among its constituents in a canonical manner, a 
partially instantiated nominal case frame can be merged with the 
previous case frame as follows: 
= Substitute any cases instantiated in the original query that 
the ellipsis specifically overrides. For instance "with two 
ports" overrides "single port" in our example, as both 
entail different values of the same case descriptor, 
regardless of their different syntactic roles. ("Single port" 
in the original query is an adjectival construction, whereas 
"with two ports" is a post-nominal modifier in the ellipsed 
fragment.) 
• Retain any cases in the original parse that are not explicitly 
contradicted by new information in the ellipsed fragment. 
For instance, "fixed media" is retained as part of the disk 
description, as are all the sentential-level cases in the 
original query, SUCh as the quantity specifier and the 
projection attribute of the query ("size"). 
• Add cases of a case frame in the query that are not 
instantiated therein, but are specified in the ellipsed 
fragment. For instance, the "fixed head" descriptor is 
added as the media case of the disk nominal case frame in 
resolving the etlipsed fragment in the following example: 
>Which disks are configurable on a VAX 11.7807 
>Any conligurable fixed head disks? 
• In the event that a new case frame is mentioned in the 
ellipsed fragment, wholesale substitution occurs, much like 
in the semantic grammar approach. For instance, if after 
the last example one were to ask "How about tape 
drives?", the substitution would replace "fixed head disks" 
with "tape drives", rather than replacing only "disks" and 
producing the phrase "fixed head tape drives", which is 
meaningless in the current domain. In these instances the 
semantic relations captured in a case frame representation 
and not in a semantic grammar parse tree prove 
immaterial. 
The key tO case-frame ellipsis resolution is matching 
corresponding cases, rather than surface strings, syntactic 
structures, or non-canonical representations. It is true that in 
order to instantiate correctly a sentential or nominal case frame 
in the parsing process requires semantic knowledge, some of 
which can be rather domain specific. But, once the parse is 
attained, the resulting canonical representation, encoding 
appropriate semantic relations, can and should be exploited to 
provide the system with additional functionality such as the 
present ellipsis resolution method. 
The major problem with semantic grammars is that they 
convolve syntax with semantics in a manner that requires 
multiple representations for the same semantic entity. For 
instance, the ordering of marked cases in the input does not 
reflect any difference in meaning (almough one could argue that 
surface ordering may reflect differential emphasis and other 
pragmatic considerations). A pure semantic grammar must 
employ different rules to recognize each and every admissible 
case sequence. Hence, the resultant parse trees differ, and the 
knowledge that surface positioning of unmarked cases is 
meaningful, but positioning of ranked ones is not, must be 
contained within the ellipsis resolution process, a very unnatural 
repository for such basic information. Moreover, in order to attain 
a measure of the functionality described above for case-frames, 
ellipsis resolution in semantic grammar parse trees must 
somehow merge adjectival and post nominal forms 
(corresponding to different non-terminals and different relative 
positions in the parse trees) so that ellipsed structures such as "a 
disk with 1 port" can replace the the "dual-port" part of the 
phrase "...dual-port fixed-media disk " in an earlier utterance. 
One way to achieve this effect is to collect together specific 
nonterminals that can substitute for each other in certain 
contexts, in essence grouping non-canonical representations 
into semantic equivalence classes. However, this process would 
requ=re hand.crafting large associative tables or similar data 
structures, a high price to pay for each domain-specific semantic 
grammar. Hence, in order to achive robust ellipsis resolution all 
proverbial roads lead to recursive case constructions encoding 
domain semantics and canonical structure for multiple surface 
manifestations. 
Finally, consider one more rule that provides additional context 
in situations where the ellipsis is of a purely semantic nature, 
such as: 
167 
)Which fixed media disks are configurable on a VAX780? 
The RP07-aa, the RP07.ab .... 
>"Add the largest" 
We need to answer the question "largest what?" before 
proceeding. One can call this problem a special case of definite 
noun phrase resolution, rather than semantic ellipses, but 
terminology is immaterial. Such phrases occur with regularity in 
our corpus of examples and must be resolved by a fairly general 
process. The following rule answers the question from context, 
regardless of the syntactic completeness of the new utterance. 
Contextual Substitution Rule 3: 
If: A command or query caseframe lacks one or more 
required case fillers (such as a missing SELECT 
field), and the last case frame in fOCUS has an 
instantiated case that meets a11 the semantic tests 
for the case missing the riller, 
THEN: t) Copy the filler onto the new caseframe, and 
Z) Attempt to copy uninstantiated case filler's as 
well (if they meet semantic tests) 
3) Echo the action being performed for impllcit 
conrlrmetion by the user. 
XCALIBUR presently has eight contextual substitution rules. 
similar to the ones above, and we have found several additional 
ones to extend the coverage of ellipsed queries and commands 
(see \[3\] for a more extensive discussion). It is significant to note 
that a small set of fairly general rules exploiting the case frame 
structures cover most instances of commonly occurring ellipsis, 
including all the examples presented earlier in this section. 
5. Acknowledgements 
Mark Boggs, Peter Anick and Michael Mauldin are part of the 
XCALIBUR team and have participated in the design and 
implementation of various modules. Phil Hayes and Steve Minton 
have contributed useful ideas in several discussions. Digital 
Equipment Corporation is funding the XCALIBUR project, which 
provides a fertile test bed for our investigations. 
6. References 
1, Allen, J.F. and Perrault, C.R.. "Analyzing Intention in 
Utterances," Artificial Intelligence. VOI. 15, NO. 3, 1980, 
pp. 14,3-178. 
2. Carbonell, J.G. and Hayes, P.J., "Dynamic Strategy 
Selection ~n Flexible Parsing," Proceedings of the 79th 
Meeting o/ the Assoctatlon for Computational Linguistics. 
1981. 
3. Carbonell, J. G., Boggs. W. M., Mauldin, M. L, and Anick, 
P. G,. "XCALIBUR Progress Report # 1: Overview of the 
Natural Language Interface," Tech. report, Carnegie- 
Mellon University, Computer Science Department, 1983. 
4. Carbonell, J.G., "Beyond Speech Acts: Meta-Language 
Utterances, Social Roles, and Goal Hierarchies," 
Preprints of the Workshop on Discourse Processes, 
Marseilles. France, 1982. 
5. Grice, H. P., "Conversational Postulates," in Explorations 
in Cognition, O. A. Norman and O.E. Rumelhart, eds., 
Freeman, San Francisco, 1975. 
6. Grosz, B.J., The Representation and Use of Focus in 
Dialogue Understanding. PhO dissertation, University of 
California at Berkeley, 1977, SRI Tech. Note 151, 
7. Hayes, P. J,, and Carbonell, J.G., "Multi-Strategy 
Construction-Specific Parsing for Flexible Data Base 
Query and Update," Proceedings of the Seventh 
International Joint Conference on Artificial Intelligence, 
August 1981, pp. 432.4,39. 
8. Hayes, P.J. and Carbonell, J.G., "A Framework for 
Processing Corrections in Task.Oriented Dialogs," 
Proceedings of the Eighth /nternationa/ Joint Conference 
on Artificial Intelligence, 1983, (Submitted). 
9. Hayes, P. J. and Carbonell, J. G., "Multi-Strategy Parsing 
and it Role in Robust Man-Machine Communication," 
Tech. report CMU-CS-81-118, Carnegie-Mellon University, 
Computer Science Department, May 1981. 
10. Hendrix. G.G., Sacerdoti, E.D. and Slocum, J., 
"Developing a Natural Language Interface to Complex 
Data," SRI International, 1976. 
11. Hendrix, G. G., "The LIFER Manual: A guide to Building 
Practical Natural Language Interfaces," Tech. 
report Tech. note 138, SRI, 1977, 
12. Joshi, A. K., "Use (or Abuse) of Metalinguistic Devices", 
Unpublished Manuscript. 
13. Kwasny, S. C. and Sondheimer, N. K., "Ungrammaticality 
and Extragrammaticahty in Natural Language 
Understanding Systems." Proceedings ot the 17th 
Meeting ol the Assocsahon for Computational Linguistics, 
1979, pp. 19-23. 
14. McDermott, J., "RI: A Rule-Based Configurer of 
Computer Systems," Tech. report, Carnegie-Mellon 
University. Computer Science Department, 1980. 
15. McDermott, J., "XSEL: A Computer Salesperson's 
Assistant," m Machine Intelligence 10. Hayes, J., Michie, 
O. and Pap, Y-H., eds., Chichester UK: Ellis Horwood Ltd., 
1982", pp. 325-387. 
16. Perrault, C, R., Allen, J.F. and Cohen, P R., "Speech 
Acts as a Basis for Understanding Dialog Coherence," 
Procceedings of the Second Conference on Theoretical 
Issues in Natural Language Processing. 1978. 
17. Rich, E., Building and Exploring User Models. PhO 
dissertation, Carnegie-Mellon University, April 1979, 
18. Ross, J. R.. "Metaanaphora," Linguistic Inquiry. 1970. 
19. Searle, J.R., "Indirect Speech ACTS," =n Syntax and 
Semantics, Volume 3: Speech Acts, P Cole and J.L. 
Morgan, eds., New York: Academic Press, 1975. 
20. Sidner, C. L., Towards a Computational Theory of Oelinite 
Anaphora Comprehension in English Discourse. PhO 
dissertation, MIT, 1979, AI-TR ~7. 
21. Waltz. D.L. and Goodman, A.B., "Writing a Natural 
Language Data Base System," Proceedings of the Fifth 
International Joint Conference on Artificial Intelligence, 
1977. pp. 144,150. 
22. Weischedel, R.M. and Black. J., "Responding to 
Potentially Unparsable Sentences," Tech. report, 
University of Delaware, Computer and Information 
Sciences, 1979, Tech Report 79/3. 
23. Wilensky, R.. "Talking to UNIX in English: An Overview of 
an Online Consultant," Tech. report, UC Berkeley, 1982, 
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