<?xml version="1.0" encoding="UTF-8"?>
<algorithms version="110505">
  <algorithm name="SectLabel" version="110505">
    <variant no="0" confidence="0.002282">
      <sectionHeader confidence="0.227858" genericHeader="abstract">
BusTUC
</sectionHeader>
      <bodyText confidence="0.316698">
- A natural language bus route oracle
Tore A m b l e Dept. of computer and information science University of Trondheim
Norway, N-7491
amble@idi, nt nu. no
</bodyText>
      <sectionHeader confidence="0.944828" genericHeader="acknowledgments">
Abstract
</sectionHeader>
      <bodyText confidence="0.995234076923077">
The paper describes a natural language based expert system route advisor for the
public bus transport in Trondheim, Norway. The system is available on the
Internet,and has been intstalled at the bus company's web server since the
beginning of 1999. The system is bilingual, relying on an internal language
independent logic representation.
In between the question and the answer is a process of lexical analysis, syntax
analysis, semantic analysis, pragmatic reasoning and database query processing.
One could argue that the information content could be solved by an
interrogation, whereby the customer is asked to produce 4 items: s t a t i o n
of departure, station of arrival, earliest departure timeand/or latest arrival
time. It
Introduction
A natural language interface to a computer database provides users with the
capability of obtaining information stored in the database by querying the
system in a natural language (NL). With a natural language as a means of
communication with a computer system, the users can make a question or a
statement in the way they normally think about the information being discussed,
freeing them from having to know how the computer stores or processes the
information. The present implementation represents a a major effort in bringing
natural language into practical use. A system is developed that can answer
queries about bus routes, stated as natural language texts, and made public
through the Internet World Wide Web
is a myth that natural language is a better way of communication because it is
&amp;quot;natural language&amp;quot;. The challenge is to prove by demonstration that an NL system
can be made that will be preferred to the interrogative mode. To do that, the
system has to be correct, user friendly and almost complete within the actual
domain.
P r e v i o u s Efforts, C H A T - 8 0 , P R A T - 8 9 and HSQL
Trondheim is a small city with a university and 140000 inhabitants. Its central
bus systems has 42 bus lines, serving 590 stations, with 1900 departures per day
(in average). T h a t gives approximately 60000 scheduled bus station passings
per day, which is somehow represented in the route data base. The starting point
is to automate the function of a route information agent. The following example
of a system response is using an actual request over telephone to the local
route information company:
Hi, I live in Nidarvoll and tonight i must reach a train to Oslo at 6 oclock.
The system, called BusTUC is built upon the classical system CHAT-80 (Warren and
Pereira, 1982). CHAT-80 was a state of the art natural language system that was
impressive on its own merits, but also established Prolog as a viable and
competitive language for Artificial Intelligence in general. The system was a
brilliant masterpiece of software, efficient and sophisticated. The natural
language system was connected to a small query system for international
geography. The following query could be analysed and answered in a split
second:
Which country bordering the Mediterranean borders a country that is bordered by
a country whose population exceeds the population of India?
(The answer 'Turkey' has become incorrect as time has passed. The irony is that
Geography was chosen as a domain without time.)
and a typical answer would follow quickly:
Bus number 54 passes by Nidarvoll skole at 1710 and arrives at Trondheim Railway
Station at 1725.
The abi!ity to answer ridiculously long queries is of course not the main goal.
The main lesson is that complex sentences are analysed with a proper
understanding without sacrificing efficiency. Any superfi-
ficial pattern matching technique would prove futile sooner or later. Making a N
o r w e g i a n CHAT-80, PRAT-89 At the University of Trondheim (NTNU), two
students made a Norwegian version of CHAT-80,called PRAT-89 (Teigen and Vetland,
1988),(Teigen and Vetland, 1989). (Also, a similar Swedish project SNACK-85 was
reported). The dictionary was changed from English to Norwegian together with
new rules for morphological analysis. The change of grammar from English to
Norwegian proved to be amazingly easy. It showed that the langauges were more
similar than one would believe, given that the languages are incomprehensible to
each other's communities. After changing the dictionary and graramar, the
following Norwegian query about the same domain could be answered correctly in a
few seconds.
Hvilke afrikanske land som hat en befolkning stoerre enn 3 millioner og mindre
enn 50 millioner og er nord
for Botswana og oest for Libya hat en hovedstad som hat en befolkning stoerre
enn 100 tusen.
Coupling the s y s t e m to an SQL database. After the remodelling, the system
could answer queries in &amp;quot;Scandinavian&amp;quot; to an internal hospital database as well
as CHAT-80 could answer Geography questions. HSQL produced a Prolog-like code
FOL (First Order Logic) for execution. A mapping from FOL to the data base
Schema was defined, and a translator from FOL to SQL was implemented. The
example
Hvilke menn ligger i en kvinnes seng?
(Which men lie in a woman's bed? )
would be translated dryly into the SQL query: SELECT DISTINCT
</bodyText>
      <equation confidence="0.500542">
T3.name,Tl.sex,T2.reg_no,T3.sex, T4.reg_no,T4.bed_no,T5.hosp_no,T5.ward_no FROM
PATIENT TI,OCCUPANCY T2,PATIENT T3, OCCUPANCY T4,WARD T5 WHERE (Tl.sex='f') AND
(T2.reg_no=Tl.reg_no) AND (T3.sex='m') AND (T4.reg_no=T3.reg_no) AND
(T4.bed_no=T2.bed_no) AND (T5.hosp_no=T4.hosp_no) AND (T5.ward_no=T4.ward_no)
2.3 T h e T h e U n d e r s t a n d i n g C o m p u t e r The HSQL was a
</equation>
      <bodyText confidence="0.947944866666667">
valuable experience in the effort to make transportable natural language
interfaces. However, the underlying system CHAT-80 restricted the further
development. After the HSQL Project was finished, an internal reseach project
TUC (the Understanding Computer) was initiated at NTNU to carry on the results
from HSQL. The project goals differed from those of HSQL in a number of ways,
and would not be concerned with multimedia interfaces . On the other hand,
portability and versatility were made central issues concerning the generality
of the language and its applications. The research goals could be summarised as
to Give computers an operational understanding of natural language. Build
intelligent systems with natural language capabilities. Study common sense
reasoning in natural language. A test criterion for the understanding capacity
is that after a set of definitions in a Naturally Readable Logic, NRL, the
system's answer to queries in NRL should conform to the answers of an idealised
rational agent.
( A translation is beside the point o.f being a long query in Norwegian.)
</bodyText>
      <subsectionHeader confidence="0.515865">
2.2 HSQL - H e l p S y s t e m for SQL A Nordic project HSQL (Help System for
</subsectionHeader>
      <bodyText confidence="0.986884">
SQL) was accomplished in 1988-89 to make a joint Nordic effort interfaces to
databases. The HSQL project was led by the Swedish State Bureau (Statskontoret),
with participants from Sweden, Denmark, Finland and Norway (Amble et al., 1990).
The aim of HSQL was to build a natural language interface to SQL databases for
the Scandinavian languages Swedish, Danish and Norwegian. These languages are
very similar, and the Norwegian version of CHAT-80 was easily extended to the
other Scandinavian languages. Instead of Geography, a more typical application
area was chosen to be a query system for hospital administration. We decided to
target an SQL database of a hospital administration which had been developed
already. The next step was then to change the domain of discourse from Geography
to hospital administration, using the same knowledge representation techniques
used in CHAT-80. A semantic model of this domain was made, and then implemented
in the CHAT-80 framework. The modelling technique that proved adequate was to
use an extended Entity Relationship (ER) model with a class (type) hierarchy,
attributes belonging to each class, single inheritance of attributes and
relationships.
Every
man that lives loves Mary. John is a man. John lives. Who loves Mary? ==&gt; John
3 Anatomy of the bus route oracle The main components of the bus route
information systems are: A parser system, consisting of a dictionary, a
lexical processor, a grammar and a parser. A knowledge base (KB), divided into
a semantic KB and an application KB A query processor, contalng a routing
logic system, and a route data base. The system is bilingual and contains a
double set of dictionary, morphology and grammar. Actually, it detects which
language is most probable by counting the number of unknown words related to
each language, and acts accordingly. The grammars are surprisingly similar, but
no effort is made to coalesce them. The Norwegian grammar is slightly bigger
than the English grammar, mostly because it is more elaborated but also because
Norwegian allows a freer word order. 3.1 Features of BusTUC For the Norwegian
systems, the figures give an indication of the size of the domain: 420 nouns,
150 verbs, 165 adjectives, 60 prepositions, etc. There are 1300 grammar rules (
810 for English) although half of the rules are very low level. The semantic net
described below contains about 4000 entries. A big name table of 3050 names in
addition to the official station names, is required to capture the variety of
naming. A simple spell correction is a part of the system ( essentially 1
character errors). The pragmatic reasoning is needed to translate the output
from the parser to a route database query language . This is done by a
production system called Pragma, which acts like an advanced rewriting system
with 580 rules. In addition, there is another rule base for actually generating
the natural language answers (120 rules). The system is mainly written in Prolog
(Sicstus Prolog 3.7), with some Perl programs for the communication and
CGI-scripts. At the moment, there are about 35000 lines of programmed Prolog
code (in addition to route tables which are also in Prolog). Average response
time is usually less than 2 seconds, but there are queries that demand up to 10
seconds. The error rate for single, correct, complete and relevant questions is
about 2 percent.
NRL is defined in a closed context. Thus interfaces to other systems are in
principle defined through simulating the environment as a dialogue partner. TUC
is a prototypical natural language processor for English written in Prolog. It
is designed to be a general purpose easily adaptable natural language processor.
It consists of a general grammar for a subset of English, a semantic knowledge
base, and modules for interfaces to other interfaces like UNIX, SQL-databases
and general textual information sources. 2.4 The TABOR Project
It so happened that a Universtity Project was starteded in 1996, called T A B O
R ( &amp;quot; Speech based user interfaces and reasoning systems &amp;quot;), with the aim of
building an automatic public transport route oracle, available over the public
telephone. At the onset of the project, the World Wide Web was fresh, and not as
widespread as today, and the telephone was still regarded as the main source of
information for the public. Since then, the Internet became the dominant medium,
and it is as likeley to find a computer with Internet connection, as to find a
local busroute table. ( The consequtive wide spreading of cellular phones
changed the picture in favour of the telephone, but that is another story). It
was decided that a text based information system should be built, regardless of
the status of the speech rocgnition and speech synthesis effort, which proved to
lag behind after a while.
The BusTUC system
The resulting system BusTUC grew out as a natural application of TUC, and an
English prototype could be built within a few months (Bratseth, 1997). Since the
summer 1996, the prototype was put onto the Internet, and been developed and
tested more or less continually until today. The most important extension was
that the system was made bilingual (Norwegian and English) during the fall 1996.
In spring 1999, the BusTUC was finally adopted by the local bus company in
Trondheim ( A/S Trondheim Trafikkselskap), which set up a server ( a 300 MHz PC
with Linux). Until today, over 150.000 questions have been answered, and BusTUC
seems to stabilize and grow increasingly popular.
</bodyText>
      <subsectionHeader confidence="0.996836">
3.2 The Parser S y s t e m The G r a m m a r S y s t e m The grammar is based on
</subsectionHeader>
      <bodyText confidence="0.994462595238095">
a simple grammar for statements, while questions and commands are derived by the
use of movements. The grammar 3
fiformalism which is called Consensical Grammar, (CONtext SENSitive
CompositionAL Grammar) is an easy to use variant of Extraposition Grammar
(Pereira and Warren, 1980), which is a generalisation of Definite Clause
Grammars. Compositional grammar means that the semantics of a a phrase is
composed of the semantics of the subphrases; the basic constituents being a form
of verb complements. As for Extraposition grammars, a grammar is translated to
Definite Clause Grammars, and executed as
such. A characteristic syntactic expression in Consensical G r a m m a r m a y
define an incomplete construct in terms of a &amp;quot;difference &amp;quot; between complete
constructs. W h e n possible, the parser will use the subtracted part in stead
of reading from the input, after a gap if necessary. The effect is the same as
for Ex-
which is analysed as
for which X is it true that the (X) person has a dog that barked?
where the last line is analysed as a s t a t e m e n t . Movement is easily
handled in Consensical Grammar without making special phrase rules for each kind
of movement. The following example shows how TUC manages a variety of analyses
using movements:
Max said Bill thought Joe believed Fido Barked. Who said Bill thought Joe
believed Fido barked? Who did Max say thought Joe believed Fido barked?
traposition grammars, but the this format is more intuitive. Examples of grammar
rules.
Who did Max say Bill thought believed Fido barked?
T h e parser The experiences with Consensical grammars are a bit mixed however.
The main problem is the parsing method itself, which is top down with
backtracking. Many principles that would prove elegant for small domains turned
out to be too costly for larger domains, due to the wide variety of modes of
expressions, incredible ambiguities and the sheer size of the covered language.
The disambiguation is a major problem for small grammars and large languages,
and was solved by the following guidelines: a semantic type checking was
integrated into the parser, and would help to discard sematica/ly wrong parses
from the start. a heuristics was followed that proved almost irreproachable:
The longest possible phrase of a category that is semantically correct is in
most cases the preferred interpretation. due to the perplexity of the
language, some committed choices (cuts) had to be inserted into the grammar at
strategic places. As one could fear however, this implied that wrong choices
being made at some point in the parsing could not be recovered by backtracking.
These problems also made it imperative to introduce a timeout on the parsing
process of embarassing 10 seconds. Although most sentences, would be parsed
within a second, some legal sentences of moderate size actually need this time.
</bodyText>
      <page confidence="0.929318">
4
</page>
      <bodyText confidence="0.999121755102041">
Example: Whose dog barked? is analysed as if the sentence had been Who has a dog
t h a t barked? which is analysed as Which p e r s o n has a dog t h a t
barked?
fi3.3 The semantic knowledge base Adaptability means that the system does not
need to be reprogrammed for each new application. The design principle of TUC is
that most of the changes are made in a tabular semantic knowledge base, while
there is one general grammar and dictionary. In general, the logic is generated
automatically from the semantic knowledge base. The nouns play a key role in the
understanding part as they constitute the class or type hierarchy. Nouns are
defined in an a - k i n d - o f hierarchy. The hierarchy is tree-structured with
single inheritance. The top level also constitute the top level ontology of
TUC's world. In fact, a type check of the compliances of verbs, nouns adjectives
and prepositions is not only necessary for the semantic processing but is
essential for the syntax analysis for the disambiguation as well. In TUC, the
legal combinations are carefully assembled in the semantic network, which then
serves a dual purpose. These semantic definitions are necessary to allow for
instance the following sentences
The dog saw a man with a telescope. The man saw a dog with a telescope.
gives exactly the same code.
% Type of question % tuc is a program % A is a real bus % B isa saturday % Nidar
is a place % D is an event Y. C was known at D
Y. E is an event in C
action(go,E), Y. the action of E is Go actor(A,E), Y. the actor of E is A
srel(to,place,nidar,E),Y. E is to nidar srel(on,time,B,E), y, E is on the
saturday B
to be treated differently because with telescope m a y modify the noun man but
not the noun dog, while with telescope modifies the verb see, restricted to
person.
The event parameter plays an important role in the semantics. It is used for
various purposes. The most salient role is to identify a subset of time and
space in which an action or event occured. Both the actual time and space
coordinates are connected to the actions through the event parameter. Pragmatic
reasoning The TQL is translated to a route database query language (BusLOG)
which is actually a Prolog program. This is done by a production system called
Pragma, which acts like an advanced rewriting system with 580 rules. In
addition, there is another rule base for actually generating the natural
language answers (120 rules). 4 Conclusions The TUC approach has as its goal to
automate the creation of new natural language interfaces for a well defined
subset of the language and with a minimum of explicit programming. The
implemented system has proved its worth, and is interesting if for no other
reason. There is also an increasing interest from other bus companies and route
information companies alike to get a similar system for their customers. Further
work remains to make the parser really efficient, and much work remains to make
the language coverage complete within reasonable limits. It is an open question
whether the system of this kind will be a preferred way of offering information
to the public. If it is, it is a fair amount of work to make it a portable
system that can be implemented elsewhere, also connecting various travelling
agencies. If not, it will remain a curiosity. But anyway, a system like this
will be a contribution to the development of intelligent systems.
</bodyText>
      <subsectionHeader confidence="0.907269">
3.4 The Query Processor Event Calculus The semantics of the phrases are built up
</subsectionHeader>
      <bodyText confidence="0.954881692307692">
by a kind of verb complements, where the event play a central role. The text is
translated from Natural language into a form called TQL (Temporal Query
Language/ TUC Query Language) which is a first order event calculus expression,
a self contained expression containing the literal meaning of an utterance. A
formalism TQL that was defined, inspired by the Event Calculus by Kowalski and
Sergot (Kowalski and Sergot, 1986). The TQL expressions consist of predicates,
functions, constants and variables. The textual words of nouns and verbs are
translated to generic predicates using the selected interpretation. The
following question
Do you know whether the bus goes
to Nidar on Saturday ? would give the TQL expression below. Typically, the
Norwegian equivalent
Vet du om bussen gaar til Nidar paa soendag ?
</bodyText>
      <sectionHeader confidence="0.933135" genericHeader="references">
References
</sectionHeader>
      <reference confidence="0.995772">
Tore Amble, Erik Knudsen, Aarno Lehtola, Jan Ljungberg, and Ole Ravnholt. 1990. Naturlig Spr~k och Grafik - nya vSgar inn i databaser. Statskontoret. Rapport om HSQL, ett kunskapsbaseret hj~lpsystem fSr SQL.
Jon S. Bratseth. 1997. BusTUC - A Natural Language Bus Traffic Informations System. Master's thesis, The Norwegian University of Science and Technology.
R. Kowalski and M. Sergot. 1986. A logic based calculus of events. New Generation Computing, 8(0):67-95.
F. C. N. Pereira and D. H. D. Warren. 1980. Definite clause grammar for language analysis. Artificial Intelligence, 0(3).
J. Teigen and V. Vetland. 1988. Syntax analysis of norwegian language. Technical report, The Norwegian Institute of Technology.
J. Teigen and V. Vetland. 1989. Handling reasonable questions beyond the linguistic and conceptual coverage of natural language interfaces. Master's thesis, The Norwegian Institute of Technology.
D. H. D Warren and F. C. N. Pereira. 1982. An efficient and easily adaptable system for interpreting natural language queries. Computational Linguistics, 8(3-4).
class="xml-element"></reference>
    </variant>
  </algorithm>
  <algorithm name="ParsHed" version="110505">
    <variant no="0" confidence="0.179864">
      <title confidence="0.9015635">BusTUC - A natural language bus route oracle</title>
      <affiliation confidence="0.631086">Tore A m b l e Dept. of computer and information science University of Trondheim</affiliation>
      <address confidence="0.986971">Norway, N-7491class="xml-element"></address>
      <email confidence="0.724262">amble@idi,ntnu.noclass="xml-element"></email>
      <abstract confidence="0.9589855">The paper describes a natural language based expert system route advisor for the public bus transport in Trondheim, Norway. The system is available on the Internet,and has been intstalled at the bus company's web server since the beginning of 1999. The system is bilingual, relying on an internal language independent logic representation. In between the question and the answer is a process of lexical analysis, syntax analysis, semantic analysis, pragmatic reasoning and database query processing. One could argue that the information content could be solved by an interrogation, whereby the customer is asked to produce 4 items: s t a t i o n of departure, station of arrival, earliest departure timeand/or latest arrival time. It</abstract>
    </variant>
  </algorithm>
  <algorithm name="ParsCit" version="110505">
    <citationList>
      <citation valid="true">
        <authors>
          <author>Tore Amble</author>
          <author>Erik Knudsen</author>
          <author>Aarno Lehtola</author>
          <author>Jan Ljungberg</author>
          <author>Ole Ravnholt</author>
        </authors>
        <title>Naturlig Spr~k och Grafik - nya vSgar inn i databaser. Statskontoret. Rapport om HSQL, ett kunskapsbaseret hj~lpsystem fSr</title>
        <date>1990</date>
        <institution>The Norwegian University of Science and Technology.</institution>
        <contexts>
          <context position="7077" citStr="Amble et al., 1990" startWordPosition="1163" endWordPosition="1166">hed in 1988-89 to make a joint Nordic effort interfaces to databases. The HSQL project was led by the Swedish State Bureau (Statskontoret), with participants from Sweden, Denmark, Finland and Norway (Amble et al., 1990). The aim of HSQL was to build a natural language interface to SQL databases for the Scandinavian languages Swedish, Danish and Norwegian. These languages are very similar, and the Norwegian version o</context>
        </contexts>
        class="xml-element"><marker>Amble, Knudsen, Lehtola, Ljungberg, Ravnholt, 1990class="xml-element"></marker>
        <rawString>Tore Amble, Erik Knudsen, Aarno Lehtola, Jan Ljungberg, and Ole Ravnholt. 1990. Naturlig Spr~k och Grafik - nya vSgar inn i databaser.  Statskontoret. Rapport om HSQL, ett kunskapsbaseret hj~lpsystem fSr SQL. Jon S. Bratseth. 1997. BusTUC - A Natural Language Bus Traffic Informations System. Master's thesis, The Norwegian University of Science and Technology.</rawString>
      </citation>
      <citation valid="true">
        <authors>
          <author>R Kowalski</author>
          <author>M Sergot</author>
        </authors>
        <title>A logic based calculus of events.</title>
        <date>1986</date>
        class="xml-element"><journal>New Generation Computing,class="xml-element"></journal>
        <pages>8--0</pages>
        <contexts>
          <context position="19193" citStr="Kowalski and Sergot, 1986" startWordPosition="3231" endWordPosition="3234">t order event calculus expression, a self contained expression containing the literal meaning of an utterance. A formalism TQL that was defined, inspired by the Event Calculus by Kowalski and Sergot (Kowalski and Sergot, 1986). The TQL expressions consist of predicates, functions, constants and variables. The textual words of nouns and verbs are translated to generic predicates using the selected interpretation. The follow</context>
        </contexts>
        class="xml-element"><marker>Kowalski, Sergot, 1986class="xml-element"></marker>
        <rawString>R. Kowalski and M. Sergot. 1986. A logic based calculus of events. New Generation Computing, 8(0):67-95.</rawString>
      </citation>
      <citation valid="true">
        <authors>
          <author>F C N Pereira</author>
          <author>D H D Warren</author>
        </authors>
        <title>Definite clause grammar for language analysis.</title>
        <date>1980</date>
        class="xml-element"><journal>Artificial Intelligence,class="xml-element"></journal>
        class="xml-element"><volume>0class="xml-element"></volume>
        class="xml-element"><issue>3class="xml-element"></issue>
        <contexts>
          <context position="12713" citStr="Pereira and Warren, 1980" startWordPosition="2103" endWordPosition="2106">mands are derived by the use of movements. The grammar 3 fiformalism which is called Consensical Grammar, (CONtext SENSitive CompositionAL Grammar) is an easy to use variant of Extraposition Grammar (Pereira and Warren, 1980), which is a generalisation of Definite Clause Grammars. Compositional grammar means that the semantics of a a phrase is composed of the semantics of the subphrases; the basic constituents being a for</context>
        </contexts>
        class="xml-element"><marker>Pereira, Warren, 1980class="xml-element"></marker>
        <rawString>F. C. N. Pereira and D. H. D. Warren. 1980. Definite clause grammar for language analysis. Artificial Intelligence, 0(3).</rawString>
      </citation>
      <citation valid="true">
        <authors>
          <author>J Teigen</author>
          <author>V Vetland</author>
        </authors>
        <title>Syntax analysis of norwegian language.</title>
        <date>1988</date>
        <tech>Technical report,</tech>
        <institution>The Norwegian Institute of Technology.</institution>
        <contexts>
          <context position="4008" citStr="Teigen and Vetland, 1988" startWordPosition="668" endWordPosition="671">ching technique would prove futile sooner or later. Making a N o r w e g i a n CHAT-80, PRAT-89 At the University of Trondheim (NTNU), two students made a Norwegian version of CHAT-80,called PRAT-89 (Teigen and Vetland, 1988),(Teigen and Vetland, 1989). (Also, a similar Swedish project SNACK-85 was reported). The dictionary was changed from English to Norwegian together with new rules for morphological analysis. The chang</context>
        </contexts>
        class="xml-element"><marker>Teigen, Vetland, 1988class="xml-element"></marker>
        <rawString>J. Teigen and V. Vetland. 1988. Syntax analysis of norwegian language. Technical report, The Norwegian Institute of Technology.</rawString>
      </citation>
      <citation valid="true">
        <authors>
          <author>J Teigen</author>
          <author>V Vetland</author>
        </authors>
        <title>Handling reasonable questions beyond the linguistic and conceptual coverage of natural language interfaces. Master's thesis, The Norwegian Institute of Technology.</title>
        <date>1989</date>
        <contexts>
          <context position="4035" citStr="Teigen and Vetland, 1989" startWordPosition="671" endWordPosition="674"> futile sooner or later. Making a N o r w e g i a n CHAT-80, PRAT-89 At the University of Trondheim (NTNU), two students made a Norwegian version of CHAT-80,called PRAT-89 (Teigen and Vetland, 1988),(Teigen and Vetland, 1989). (Also, a similar Swedish project SNACK-85 was reported). The dictionary was changed from English to Norwegian together with new rules for morphological analysis. The change of grammar from English t</context>
        </contexts>
        class="xml-element"><marker>Teigen, Vetland, 1989class="xml-element"></marker>
        <rawString>J. Teigen and V. Vetland. 1989. Handling reasonable questions beyond the linguistic and conceptual coverage of natural language interfaces. Master's thesis, The Norwegian Institute of Technology.</rawString>
      </citation>
      <citation valid="true">
        <authors>
          <author>D H D Warren</author>
          <author>F C N Pereira</author>
        </authors>
        <title>An efficient and easily adaptable system for interpreting natural language queries.</title>
        <date>1982</date>
        class="xml-element"><journal>Computational Linguistics,class="xml-element"></journal>
        <pages>8--3</pages>
        <contexts>
          <context position="2701" citStr="Warren and Pereira, 1982" startWordPosition="458" endWordPosition="461">r telephone to the local route information company: Hi, I live in Nidarvoll and tonight i must reach a train to Oslo at 6 oclock. The system, called BusTUC is built upon the classical system CHAT-80 (Warren and Pereira, 1982). CHAT-80 was a state of the art natural language system that was impressive on its own merits, but also established Prolog as a viable and competitive language for Artificial Intelligence in general.</context>
        </contexts>
        class="xml-element"><marker>Warren, Pereira, 1982class="xml-element"></marker>
        <rawString>D. H. D Warren and F. C. N. Pereira. 1982. An efficient and easily adaptable system for interpreting natural language queries. Computational Linguistics, 8(3-4).</rawString>
      </citation>
    </citationList>
  </algorithm>
</algorithms>