COLING 82, Z Horeck~ (ed.) 
North.Holland Publishing Company 
© Academi~ 1982 
REFERENTIAL NETS WITH ATTRIBUTES 
Christopher U. Habel * 
ODe of the essential problems in natural language production 
and understanding is the problem of processing referential 
relations. In this paper I describe a model for representing 
and processing referential relations: referential nets with 
attributes. Both processes (analyzing and generating 
referential expressions) are controlled by attributes. There 
are two types of attributes, on one hand, the ones to the 
internal substitutes of the objects spoken about, on the other 
hand, the ones to the descriptions of these objects. 
I. BASIC NOTIONS: KNOWLEDGE AND SEMANTIC REPRESENTATION 
It is a well-known fact that (computational) models of human language production 
and understanding have to take the knowledge of the speaker and the listener into 
consideration. Thus, one of the main problems is to describe and represent this 
knowledge and to distinguish relevant subtypes. A suitable classification which I 
described in detail in Habel \[7\] distinguishes three subtypes: 
- knowledge of facts or assertions, e.g. of states of the world, events, etc., 
the "factual knowledge', 
- knowledge of rules, e.g. of rule-like relations between objects or states of 
the world (or classes of such entities), the "inferential knowledge', 
- knowledge of objects, e.g. of persons in the world, the "referential 
knowledge'. 
(In this paper I give emphasis to the third type: referential knowledge 
represented by "Referential Nets'). 
The common core for representing all these types of knowledge is the "semantic 
representation language" SRL. From the formal point of view SRL is a 
(propositional) symbolic language as described by Kalish/Montague \[8\]. Well-formed 
SRL-expressions are generated by normal (recursive) formation rules. I 
distinguish - as usual - two kinds of meaningful expressions in SRL, terms and 
formulas. Thus we define: 
TER - the set of well-formed terms 
FOR - the set of well-formed formulas 
SRL = <FOR, TER> 
For the purpose of knowledge representation SRL contains some specific operators, 
e.g. 
on the factual level: tenses, beliefs, ...... 
on the inferential level: entailment relation,... 
on the referential level: description operators of various types. 
Since SRL is a representation language, I now have to treat the central question 
of "representation theory': What kinds of entities are represented by the 
different entities of SRL? Here I follow - with minor changes, which I will not 
discuss in this paper Miller \[I0\]: The expressions and entities of SRL 
represent cognitive concepts. The operators correspond to different types of 
"concepts" in the Miller-approach, e.g. predicative , nominal and modifying 
concepts (this third class are the "operators" of Miller.). E.go by means of 
description operators it is possible to construct nominal concepts from 
101 
102 CH. U. HABEL 
predicative concepts or other nominal concepts. 
I shall now illustrate SRL with an example. In understanding and representing the 
sentence 
(i) I will meet Barbara in the university tomorrow. 
the act of referring to "I", "Barbara", and "the university" is to be processed, 
i.e. the (obJect-)orientation to them is the interesting problem from the 
referential point of view. The SRL representation of (i) is 
(2) time (meeting (l,Barbara, ETA(x) :university(x) ),tomorrow) 
The arguments of "time" and "meeting" present the most relevant types of 
referential operators: "I" and "tomorrow" are deictic substitutes (personal or 
temporal), Barbara is a proper name and the expression "ETA(x): university(x)" is 
built up from the nominal concept "'university" (representing a class of 
institutions for education and science) and the variable-binding description 
operator "ETa'. "ETA(x): p(x)" has the meaning "'an element from the class 
{x/p(x)>". ETA is an indefinite analogy to the IOTA-operator of formal logics 
(Similar operators are introduced by Hilbert as EPSILON- or ETA-operator.). The 
semantics of the description operators is given by a set of inference and 
evaluation rules. E.g. there is an inference rule which relates the ETA- 
expressions to expressions with existential quantification: 
(3) p(ETA(x) : q(x) ) ~ EX x : p(x) & q(x) 1" 
Some evaluation rules will be described in the following chapters, e.g. "creation 
of a referential object'. (Both types of rules are described in detail in Habel 
\[5\], \[6\].) Thus, ETA is the formal representative of one of the meanings of 
indefinite articles. 
Further descriptions of the objects mentioned in (i) or in the SRL expression (2) 
can be generated by (focussing) transformations similar to the solution of 
algebraic equations: The university mentioned above is also the one described by 
(4) ETA(x) :time ( meeting(l,Barbara, university(x)),tomorrow ) 2~ 
or the natural language equivalent "a (the) university where Barbara and I will 
meet tomorrow". (The uniqueness of the ETA-description depends on the 
sltuatlonal/textual context.) 
Before we pass on to a detailed description of "referential nets', I will make a 
short remark on discourse and communication. As mentioned above human language 
production and understanding is based on the speaker-listener's knowledge of the 
language, the world and particularly the participants in the communication. Thus, 
I assume a discourse model 3* which is based Dn tripartite knowledge (namely 
factual, inferential, and referential), each of these types is represented by 
structured sets of SRL-expressions. 
\ 
2. THE REFERENTIAL NET 
Processing, e.g. storing or retrieving, referential relations is executed by a 
particular component of the discourse processing system, the "referential 
procedures" (ReP). The RePs work on a memory structure which is adequate for the 
representation of knowledge about objects, the "referential net" (RefN) 4*. A RefN 
consists of entities of three different types: 
- referential objects (RefOs), which are the internal substitutes for the objects 
spoken about, 
- descriptions, i.e. terms of SRL which describe the RefOs, 
- attributes, i.e. properties of the description-relation between a RefO and one 
of its descriptions or properties of the RefO (see chap. 3). 
After detecting a new indefinite description (as ETA(x) : unlversity(x)) ReP 
creates a new "referential object'" (RefO). During the discours6 (after the 
identification process) further descriptions of the same RefO will be linked to 
this RefO. (The relation among the descriptions of the same RefO is the wellknown 
relation of eoreference,) ~us we have, for example, the following set of 
descriptions of the RefO mentioned above : 
(5) r.l~.~ d. II--ETA(x) : university(x) 
d.12-- ETA(x): time (meeting(l'Barbara'university(x))'t°m°rr°w) 
d. I3-- IOTA(x) : professor-at(Barbara,university(x)) 
REFERENTIAL NETS WITH ATTRIBUTF_~ 103 
For the description of the referential net I use SRL and in addition a "finite but 
extendable" set, REFO, of "referential objects'. The referential objects are 
seen as a kind of basic term of SRL. The set REFO is analogous to the set of 
variables. The phrase "finite but extendable" is used to emphasize the dynamic 
aspect of the set REFO and the RefN. REFO consists of exactly those RefOs that are 
actually needed. It is necessary to distinguish two types of terms, one type 
which consists of the mental representatives, i.e. the RefOs, and the other which 
contains those terms which function as descriptions. Naming this set by D-TER we 
have TER - REFO U D-TER. Thus, referential nets, RefNs, can he defined as 
(6) RefN c D-TER x REFO • 
For <d-ter, r.i> 6 RefN I also use "d-ter deser r.i'" , "d-ter is a description 
of r.i". In this way a description-relation is defined on the basis of the RefN. 
By means of referential nets it is possible, e.g. to arrive at one object (i.e. 
RefO) via different aspects, i.e. different descriptions, of this object. It is 
only by such aspects (cp. Schank's \[II\] way of memory discrimination), that a 
system is able to choose "'a best description" of the objects which are the theme 
of the discourse (see below). The referential net (5) is simplified in two 
crucial points, first, that the descriptions of r.l operate on MSRL ~pressions 
and not on RefOs, too. But this can be treated similarly to the focussing process 
of (4), which can be formallzed now: 
(7) p(r.i) 8--- r.i -- ETA(x) : p(x) 
Using (7), the descriptions can be solved with respect to all RefOs, i.e. all 
arguments are filled by RefOs or open terms. Thus we can derive (8) from (5): 
(8) r.l~----- d. II-ETA(x) : university(x) 
d.12-ETA(x): time (meeting(r.2, r.3, unlverslty(x)), r.4) 
d.13-IOTA(x) : professor-at(r.3, universlty(x)) 
r.2-- d.21-"I'" 
r.3 -- d.31--Barbara 
r.4-- d.41-"tomorrow" 
Secondly, ReP has tO explicate the referential links of deictlc substitutes, e.g. 
"r" refers to the speaker, etc.. " " stands for the specific ReP which evaluates 
deictlc expressions, i.e. which ins~antiates deictic ~xpressions with RefOs, e.g. 
"I'" - SPEAKER(l) (cp. fn 6.). By the same methods new RefOs for "we" can be 
created, e.g. in the processing of "There we will discuss some papers." (We = 
Barbara + I) 
3. ATTRIBUTES IN REFERENTIAL NETS 
I will now extend the basic two-place relation between RefOs and descriptions to 
the more adequate concept of a many-place referential relation. The additional 
places will be called "attributes'. In the first step of extention I give 
emphasis to "attributes of descriptions'. They represent properties of the 
description relation, i.e. of pairs <d, r> E RefN. Thus, the extention to an 
attributed RefN (ARefN) uses a set ATT of attributes and changes (6) to 
(9) ARefN c ATT x D-TER x REFO . 
For <att, d, r > C ARefN I also say "'att is an attribute of d with regard to r". 
Some possible attributes are (Note the fact that this list is not complete and not 
fully adequate): 
- syntactic and semantic features of the description, e.g. gender, number, sexus, 
etc. 
- numerical values, e.g. "grades of relevance of a description", "degrees of 
"being the TOPIC / being in the FOCUS" ", "recency". 5* A simple strategy for 
de-/coding is: '~se/try the description or RefO with highest degrees !'" 
- names of persons, e.g. participants of earlier discourses. By this attribute it 
is possible to find a description relevant to speaker and listener (Cp. Clark / 
Marshall's \[I\] co-presence triples). 
- situations in which the description / RefO Is relevant or was introduced (cp. 
Webber's \[12\] "evoke°-predicate). 
- links to the factual knowledge; thus we can answer such questions as "What will 
Barbara do tomorrow?" 
104 CH. U. HABEL 
Before I explain the concept of "attributes to descriptions" by some examples, I 
will new sketch some aspects of function and statue of the attributes. Firstly, in 
both processes, analysis as well as generation of referential expressions, it is 
necessary to take into consideration a set of alternatives. All of them are 
possible candidates to be the referent (in analyzing) or to be a good description 
(in producing) respectively. The goal of the ReP is to choose exactly one from the 
alternatives, namely "the best'. It is obvious that trying to choose the best can 
fail. Then the decision has to be revised afterwards. (But this is a total 
different problem.) In other words, the function of the attributes is to point to 
the most appropriate (or being more careful: to that which seems to be the most 
appropriate) of the alternatives. Secondly, I think that, on one hand, knowing and 
processing attributes is part of human natural language processing, and therefore, 
these attributes have to be part of the discourse processing model. On the other 
hand, knowledge of attributes is different (cp. the list of possible attributes, 
above) from the factual or referential knowledge. Thus, I propose a strict 
separation between descriptions and their attributes. This strict distinction 
contrasts to Webber's \[12\] solution: her use of the "evoke'-predieate mixes the 
concepts of descriptions and their attributes in a cognitive inadequate manner. 
Now I shall continue with examples of the use of attributes • Let us suppose a 
situation in which a questioner Q asks: 
(I0) Where can I study Computational Linguistics? 
and the answerer A knows that the university which is (internally) represented by 
r.l is a good university to study CL. The selection of the best description of r.l 
depends on Q and A (and the situational context). I assume the following 
attributes to the descriptions of r.l (from (5), (8)): 
(ii) descr, general relevant to: time of relevance: 
-d.ll "unspecified" 
-d.12 SPEAKER(I), LISTENER(1), Barbara NEIGHBOR(r.4) 6* 
-d.13 SPEAKER(1), LISTENER(I), KNOW(Barbara) always 
(II) describes a situation, in which the name / location of the university in 
question is not represented, e.g. since the information about the possibility to 
study CLwas given by an earlier utterance of Barbara "We have some courses in CL" 
but A (whose RefN is represented by (ii)) does not know where Barbara teaches. The 
best description can be chosen by comparing the attributes of Q with those of the 
descriptions of r.l. If Q knows Barbara, .i.e. <KNOW(Barbara)> ATT (Q) 7*, then 
the best description will be: 
(12) d.13 - "The university where Barbara teaches (as a professor)." 
Ranking d.13 higher / better than d.12 depends on the dimension "time of 
relevance'. Furthermore, if Q knows more about r.l it is possible that Q will 
react with, 
(13) "Well, at Amherst.'" 
and now A is able to extend hls/her RefN with a further description of r.l 
(14) r.l - d.14 - Amherst -- "general high relevance" "always" 
(This attribute depends on the fact that proper names have high relevance in 
general.) 
Anagously we can use attributes in the decoding process. Look at the following 
pair of sentences (similar to (I)). 
(15) a. I will meet the head of the linguistic department tomorrow. 
b. She is a specialist for Montague grammar. 
To solve this referential problem ( and not to be puzzled by the pronoun "she" ) 
we need further background knowledge, e.g. "Barbara is the head of the linguistic 
department.". With this prior knowledge and the additional (theoretical) concept 
of "attributes to RefOs" 8* as described in 
(16) "female" "local TOPIC'- r.3-- d.31- Barbara 
d.32- IOTA(x) : head-of(x ,linguist. dept.) 
the referential problem of (15) is easy to solve. A system (human listener or 
machine) has to match the pattern corresponding to the pronoun "she" ~Ich is 
induced by the context (15.5) against the descriptions, their attributes and the 
attributes of the RefO's. The crucial attribute is here "female" for both "she" 
and "r.3". 
This type of congruence between gender of the pronoun and sexus of the RefO, i.e. 
REFERENTIAL NETSWITHATTRIBUTES 105 
between attributes of descriptions and those of the RefOs, is very important in 
German. In spite of the syntaetlc ineongruence (neutr. vs. fem.) it is possible 
(in colloquial German) to say: 
(17) Ich traf gestern ein Maedchen. Sle hatte rote Haare. 
I met yesterday a glrl . She had red hair . 
neutr. ~ fem. 
4. CONCLUDING REMARKS 
By means of an extended referential net (w~th attributes both of descriptions and 
RefOs) it is possible to describe how to store and process referential entities 
(and expressions) in a cognitive adequate and powerful way. 
Following the principles and concepts described above a system for anaphora 
resolution has been implemented (Guenther \[3\]), which will be a component of the 
next version of the BACON-system (cp. fn 3). 
FOOTNOTES: 
* Parts of the first draft of this paper were prepared during my work with the 
project "Automatic Construction of Semantic Nets" at the Technical University 
of Berlin. My current research on "referential nets" has been supported by the 
DFG (German Research Foundation). Author's address: Blelbtreustr. 36 a, D-1000 
Berlin 15; Fed. Rep. Germany. 
I* From a formal point of view "inference rules" are transformation rules on SRL. 
Their cognitive and philosphlcal status, which is analogous to Miller's \[I0\] 
"conceptual entailment', is described in }{abe\], \[7\]. 
Here, i,e. in (3), and in the focussing rule (7) "p" stands for all types of 
concepts which are represented by open formulas. 
2* The focussing transformation mentioned above is based on the concept of 
referential nets and therefore its description will be postponed to the 
following chapter. In (4) a special "bar-convention" is used, which I do not 
want to explain in detail here. In case a term is necessary as argument, e.g. 
of "meeting", the "bar" will change the open formula "p(x)'" to an "open term" 
3* Cp. }{abel \[7\] and Gust / Hahel / Rollinger \[4\]. This model is the theoretical 
basis of the natural language QAS BACON (Berlin Automatic COnstruction of 
semantic Nets), developed at the Technical University of Berlin, which was 
supported by a grant from the Federal Government since 1978. It should not be 
confused with the BACON-system of Carnegie-Mellon University (we chose the same 
name at the same time). 
4* The concept of referential nets is similar to discourse referents (Karttunen 
\[9\]), reference diaries (Clark/Marshall \[1\]) and discourse models (Webber 
\[12\]). The most relevant difference between referential nets and the other 
approaches and the main advantage of referential nets consist in the further 
attributes described below. 
Note the fact that the acrony=s ReP, RefN, etc. can stand for the respective 
concept, e.g. "referential net', as well as for a specific instantlation, e.g. 
the RefN (5) or (8). Furthermore ReP concerns the system of referential 
procedures as well as the individual procedures. In all these cases the meaning 
of the acronym is obvious through context. 
5* In this paper TOPIC / FOCUS are used in an informal and intuitive way. (For a 
detailed investigation of these concepts cp, Grosz. \[2\]) Note that the 
attribute "time of relevance" i:~ (ii) is part of TOPIC / FOCUS. 
106 CH.U. HABEL 
6* SPEAKER(l) stands for "the speaker of utterance (I)', i.e. this attribute 
gives more information than Webber's \[12\] "evoke(l)'. "KNOW(_)" represents 
"people knowing _'. "NEIGHBOR(--)" stands for "points / periods of time near to 
the point of time being the argument'. I do not want to explain the underlying 
"logic of time" here. 
7* I will not explain the concept of "attributes of a person / participant" here. 
I use it in a straightforward and intuitive manner. 
8* The extention to attributes of RefOs is analogous to that from (6) to (9): 
AARefN c ATT. I x D-TER x (REDO x ATT.2) • 
ATT.I stands for the attributes of descriptions, ATT.2 for the attributes / 
properties of RefOs. AARefN is a "double attributed RefN'. Note the fact that 
same of the attributes of the RefOs will be computed from those of 
descriptions~ e.g. "female" from a attribute of "Barbara'. 

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