The role of cognitive modelling in general and that of frames in particular in terminology theory and practice
Full text
Terminologija | 2010 | 17 2 1 The role of cognitive modelling in general and that of frames in particular in terminology theory and practice WIlly MaRtIN Lexicology/TerminologyresearchGroup VrijeUniversiteitamsterdam 1. INTRODucTION AND SuRVEy In this paper cognitivemodellingwill be understood as the systematic representation of knowledge within a certain subject or knowledge field. The term model will be taken here as a background against which, or a system by means of which, knowledge can be organised. A TD (Terminological Database) will, among others, be regarded as the description of a knowledge field by means of a terminology. A terminological dictionary, as opposed to a terminological database, will be considered as secondary to the latter, in other words, dictionaries will be regarded as derivations (front-ends) of underlying databases. The paper itself will consist of three parts. First of all, different levels of cognitive modelling will be distinguished and illustrated. Secondly, a frame-based approach to one of the levels, viz. that of terms/concepts, will be discussed. Thirdly and finally, the approach advocated will be confronted with a set of important terminological issues in order to situate and evaluate it. 2. LEVELS OF cOGNITIVE MODELLING In order to function well (so that knowledge can be [easily] acquired and [properly] used), I will argue that a TD needs to be organised at, at least, three levels, viz. • that of the domain, • that of the database and • that of the terms/concepts. In what follows therefore I will deal with • domain modelling (modelling at the higher level, the so-called macrostructural level);
2 2 W. Martin | Theroleofcognitivemodellingingeneralandthatofframes... • data modelling (modelling at the intermediate level, that of the entities and relations in a database, the so-called mediostructural level); • term/concept modelling (modelling at the lowest level, that of the terms and the concepts, the so-called microstructural level). In order to make clear what is meant I will illustrate the respective levels one by one in the next sections. 2.1. Domain modelling If a terminological database is meant to deal with knowledge and with its management, then it has to provide for a model representing the way how the ‘(sub-)world’, the domain, is organised/structured. So, for instance, in medicineone basic concept, viz. that of disease(nosologyin figure 1 below) structures the whole field. It is the central organising principle within this ‘world’. If one talks about body-parts here, it is because of the fact that they are/can be affected; if one talks about organisms the same applies; therapeutic procedures only make sense when they refer to diseases and so are symptoms (findings), causes (etiology) etc. Everything in the medicinal world is linked directly or indirectly (via other concepts) to the central concept disease.The amount and granularity of the information given about other concepts is defined by this direct or indirect relationship. Domain modelling, therefore, is aconditiosine quanonwithout which it is impossible to construct a terminological database. In figure 1 a simplified schematic representation is given of such domain modelling for medicine[for more details see Martin e.a. 1991]. As one can observe, all main categories are centripetally related to disease (nosology): anatomy (MEMF) and organisms by the ‘affect’ relation, etiology by the ‘caused by’ relation, findings by the ‘symptoms’ relation, therapeutic procedures by the ‘treat’ relation etc. Typically then the medicinal domain is a domain which is well delineated and centralised: a domain with one central/core category to which all other categories are related. It goes without saying that taking the same objects and putting them into a different domain (‘drugs’ in medicineversus the same category in pharmacy)alters the structure of the field and the amount and character of the knowledge that should be expressed. That is, among others, one of the reasons why domain modelling is crucial when starting with the construction of a TD and dealing with knowledge representation.
Terminologija | 2010 | 17 2 3 Figure 1: Example of a ‘delimited’ centralised domain (medicine) Not all domains show the same kind of structure though. So, for instance, in figure 2 an example is given of the domain of educational systems,which has an embedded or onion-like structure. There one can argue that all the tunics together form the whole (onion) and that (therefore) one simply cannot restrict oneself to, for instance, the innermost tunic, but will have to select from all tunics (circles) if one wants to come to grips with the domain of educational systems as a whole. As the preceding examples show, subject fields/domains are not always ordered hierarchically (according to is-a or part-of relations) as one may expect at first sight, because of biological models with their strict taxonomic order. Moreover, sometimes domains are rather fuzzy. Whereas, for instance, the treated domain of medicineis rather well delineated, that of businessis much less so, such as figure 3 illustrates. Although one can observe that the domain businessimplies the interaction between a company and both its external partners and its internal parts (P = production section, F = financial section, S = selling section, A = administrative section) and although in both interactions selling
2 4 W. Martin | Theroleofcognitivemodellingingeneralandthatofframes... Figure 2: Example of an onion-like organised domain (educational systems) Figure 3: Example of a diffuse centralised domain (business) (business) and (industrial) partners/parts come first, yet the domain as such remains diffuse, although it is centrally organised. Whatever the domain, having a good insight into the superor macrostructure of the field is a necessary condition both to better delineate the subject-field itself and to organise/represent knowledge within that field by means of a TD.
Terminologija | 2010 | 17 2 5 2.2. Data modelling under data modelling I here understand the modelling of data as in a database, implying • the definition of the entities in the model and their relationships (e.g. terms, concepts, collocations and the relations/links that exist between them) and • the definition of the data categories for the different entities (both the attributes and the [domains of their] values). Indeed, in a data model one does not only have to make clear what one wants to represent from a contents point-of-view (see 2.1 above: the general framework or macrostructure of the world/domain to be represented), but also howone will do so: by means of which formal objects, entities and relations. In a project called DOT (acronym for Dutch Databank overheidsterminologie: Database Government Terminology; see Maks e.a. 2000 and Maks e.a. 2001) the system needed as entities: concepts, terms, collocations and links in order to represent terms, the use of terms as in collocations, the relationship between terms such as (near) synonymy, (near) equivalence and the like. Figure 4 can give an idea of what is meant. As one will observe, different graphic firms are used to distinguish between: • concepts (c), • terms (T) and • collocations (cOLL). Furthermore, a clear distinction is made (see horizontal broken line) between terms and concepts, implying that concept entities correspond to semantic units expressed by one or more terms in one or more languages. Term entities represent one term together with its full linguistic description including its usage. collocation entities do the same for collocations. There are several kinds of links also: both explicit (the full lines in the scheme) and implicit links (the broken lines). An example of an explicit link (one the terminologist has to explicitly fill out) is that between a concept and a term, or that between a concept and a concept (with values such as NEARSyN, hyPER, hyPO, REL(ATED)). Implicit links are links that the system can derive automatically: because of the fact that terms are linked to concepts and that pragmatic values are specified per
2 6 W. Martin | Theroleofcognitivemodellingingeneralandthatofframes... Figure 4: Entities, links and relations in DOT (based on Maks e.a. 2000, see also Maks e.a. 2001 for more information) term, the relations between terms (both intraand interlingual ones) need not be mentioned explicitly, but can be ‘calculated’, leading to full synonymy, complete translation equivalence, restricted translation equivalence, and near translation equivalence. The advantage of keeping the conceptual and the linguistic (terminological) level apart is, among others, that the description of a term in one language does not influence the description of its so-called translation equivalent in another language. In other words, one can work now with unilingual entries, meaning that the terms of one language can be described independently from that of another one and yet can be linked with each other via the conceptual level. In figure 5 the difference between unilingual and multilingual entries in a multilingual database is schematically represented.
Terminologija | 2010 | 17 2 7 unilingual entries (entries within one language) can be linked with other unilingual entries (entries from one or more languages) without one language biasing the description of the other. In multilingual entries one entry contains all information for all languages. The problem then is that differences at the conceptual level are blurred if terms from different languages are treated as translation equivalents without being fully equivalent. The above not only makes clear that one cannot construct a data model without having any notion about the (terms occurring in the) domain one is dealing with, but also that one should not abstract away from the tasks one wants to carry out with the databank (as in the case of DOT: comparing law systems and translating ‘governmental’ texts). Data modelling not only comprises the definition of entities, but that of the data/information categories that ‘decorate’ these entities as well. In the next section I will deal with one of these entities, viz. concepts. 2.3 Concept modelling In the preceding section I have already pointed at some of the advantages of a conceptual approach. One of the problems encountered here is how to represent concepts (taken as mental building blocks to organise knowledge with). If one accepts that the (conceptual) meaning of a term is, as a rule, represented by its definition, then one could represent the meaning/definition/concept expressed by the term using a semantic network Figure 5: Multilingual versus Unilingual Entries
2 8 W. Martin | Theroleofcognitivemodellingingeneralandthatofframes... as a model (see, for instance, Fraas 1998: 433 ss.). In Martin 1998 semantic networks are represented in the form of frames and, among others, used as definition models. In the next part I will further elaborate upon the role of frames and on that of a frame-based approach to terminology. 3. A FRAME-BASED APPROAch TO cONcEPT MODELLING Frames are taken here in the AI sense of the word, following the Minskyan tradition (see, for instance, Minsky 1975). In this sense they are structures representing background, implicit, stereotyped knowledge which is necessary in order to understand concepts and meaning. AI frames à la Minsky have a slot-filler format. From this point-of-view a frame is a set of general conceptual categories or relations (slots) followed by specifications (fillers). In order to make clear what is meant, I will turn to a concrete example. Semantic frames are type-bound, meaning that they are bound to certain concept types. concept types need to have been established in the domain modelling phase (see section 2.1. above). For instance, in the domain of government terminology a type such as allowancewill occur. The frame-like representation for allowancelooks as follows (see also Martin and heid 2001: 58): Table 1: Frame for the type allowance allowance Slot PARAPhRASE OF SLOT goal what the allowanceis meant for source who pays the a. beneficiary who receives the a. reason why the a.is paid size what the amount of the a.is time when the a.is paid periodicity how many times the a.is paid way in which form the a.is given condition under which conditions the a.is given In the world of socialservicesthen, the concept pensionwill be regarded as a token of the type allowance.
Terminologija | 2010 | 17 2 9 The underlying frame for this type will consist of the following slots/ elements: • beneficiary whogetstheallowance? • source whogivesthea.? • goal whatisthea.givenfor? • reason/ground onwhichbasisisthea.given? • size whatisthesizeofthea.? • periodicity howmanytimesisthea.given? • time whenisthea.given? • way inwhichform(e.g.moneyorothervalues)isthe a. given? • condition whicharetheconditionsunderwhichthea.is given? A definition derived from this frame could read: A pensionis an amount of money, fixed by law or (insurance) agreement, paid to someone (a pensionableor his widowor orphans)by someone else (a [former] employer,an executiveorganisation),periodically (e.g. everymonth)to provide for the cost of living, after one has retired either because of having reached the fixed age of retirement or because of invalidity, if a contribution has been paid for during the term of office. Of course both the concrete form and contents of the definition itself strongly depend on the user they are meant for. however, if one takes for granted that the conceptual meaning of a term is, as a rule, represented by its definition, then cognitive models such as frames can certainly be of great help in systematising definitions. In the next section I will try to make clear that cognitive modelling in general and a framebased approach in particular, go beyond that, and have an impact not only on the realm of definitions and concepts, but in that of terminological theory and practice in general as well. 4. DIScuSSION: IMPAcT OF cOGNITIVE MODELLING ON ThEORy AND PRAcTIcE OF TERMINOLOGy The basic claim put forward in this paper has been the following: If terminology has to do with the • acquisition, • representation and • application