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CW d }=zc- DGe P:Retrait1 }H=|,.H DGeP }6=~-/6 DGeN }-=.0- DGeN }?=/? DGe }=h` EGe P:heading 1 HHˆ7HHˆ 3G e HHˆ7;HHˆ22l HHˆ7HHˆ 5G e HHˆ77HHˆ44l HUV 7HUV 7W` HUV 795HUV 66l H$ 7H$ 9W ` H$ 77H$ 88l HUV 7HUV ;G!e HUV 7=3HUV ::l H$ 7H$ =G"e H$ 7;H$ <<l HHˆ7HHˆ‡;55?$G`5Conceptual Modelling of Narrative Texts : An Example %Sc`Gian Piero ZARRI &K`-Centre National de la Recherche Scientifique 'h` EHESS - CAMS (`54, boulevard Raspail )`75270 PARIS Cedex 06, France *`zarri@cams.msh-paris.fr +hD` ,u`Abstract  -Sc{ aNKRL (Narrative Knowledge Representation Language) is a conceptual language which intends to pro0a|hvide a normalised, description of the semantic contents (the meaning) of NL narrative texts. We introiduce firstly the general architecture of NKRL, and we give some examples of its characteristic features. @XWe supply then the detailed NKRL coding of a section of an actual narrative document. .uȮ` Introduction /Sc٧ qIn the so-called narrative, the main part of the information content consists in the description of facts or 0~mevents which relate the real or intended behaviour of some actors (characters, personages, etc.) : these otry to attain a specific result, experience particular situations, manipulate some (concrete or abstract) matesrials, deliver or receive messages, etc. Please note that, in this sort of texts, the actors or personages are not inecessarily human beings ; we can have narrative documents concerning the vicissitudes in the journey of ma nuclear submarine (the actor or the personage) or the various avatars in the life of a commercial prod@uct. 0` !1 kBeing able to represent the semantic content of narrative information i.e., its key meaning in a genmeral, accurate, and effective way is both conceptually relevant and economically interesting. In this paper, kwe suggest that at least some directions for formally establishing a standard vehicle for representing the ksemantic content of narrative information could be found in the solutions adopted in a conceptual language elike NKRL (acronym of Narrative Knowledge Representation Language), expressly created for describing l(and actually exploiting) narrative documents. The representation principles used in NKRL have, in, fact, a jlong history of successful, concrete applications which go back to the Seventies ; recent implementations `have been realised in the framework of two European projects : NOMOS, Esprit P5330, and COBALT, @ LRE P61011. 2` 3` 4uY`1The architecture of NKRL 5ScS` 69k`NKRL is a two layer language. 7` 8u՟`1.1The lower layer 9Sc昣` : lThe lower layer of NKRL consists of a set of general representation tools which are structured into several em@)integrated components, four in our case. ;` !< jThe definitional component of NKRL supplies the tools for representing the important notions (concepts) jof a given domain ; in NKRL, a concept is, therefore, a definitional data structure associated with a symbolic label like  physical_entity ,  human_being ,  taxi_  (the general class including all the taxis, not a specific }cab),  city _, etc. These definitional data structures are, substantially, frame-like structures ; moreover, all the mNKRL concepts are inserted into a generalisation/specialisation (tangled) hierarchy that, for historical rea@\sons, is called H_CLASS(es), and which corresponds well to the usual ontologies of terms. =` a> iTo give rise to well-formed ontologies of NKRL concepts, the original notions must be conceived in terms of sets and subsets where, as usual, asserting that  a  pertains to the set  A , ( a  :  A ) is equivalent to assert that  a  is characterised by the type  A . 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Instances are still, of course, directly associated as terminal symbols with particu0idlar H_CLASS terms, but they are in the domain of another NKRL component, the enumerative component, dsee below. Moreover, a fundamental assumption about the organisation of H_CLASS concerns the differjentiation between notions which can be realised (instantiated) directly into enumerable specimens, like nchair (a physical object) and notions which cannot be instantiated directly into specimens, like gold k(a substance) please note that a notion like white gold is a specialisation (subset) of gold, not an dinstance. The two high-level branches of H_CLASS stem, therefore, from two concepts that adopting qthe terminology used in (Guarino, Carrara and Giaretta 1994) we have labelled as  sortal_concepts  and "1mnon_sortal_concepts , see also Figure 5 in subsection 3.2 below. The specialisations of the former, like chair_ ,  city_  or  european_city , can have direct (immediate) instances (chair_27, paris_), whereas the spe"cialisations of the latter, like  gold_ , or  colour_ , can admit further specialisations, see  white_gold  or  red_ , E"but do not have direct instances. ?e !@%eThe enumerative component of NKRL concerns then the formal representation of the instances (concrete eexamples, see lucy_, wardrobe_1, taxi_53, paris_, not subsets) of the sortal concepts of H_CLASS. In hNKRL, their formal representations take the name of individuals. Individuals are characterised by the hfact of being countable (enumerable), of being associated with a temporal dimension (and, often, with a hspatial dimension), and of possessing unique symbolic labels (lucy_, wardrobe_1, taxi_53) ; see, below, lsubsection 3.1 for the representation of collections of instances. Throughout this paper, we will use the Efitalic type style to represent a  concept_ , the roman style to represent an individual_. Ae !B %hWe can note immediately that, in NKRL, the concepts and their instances (individuals) are kept conceptumally distinct even if they are represented using the same data structures. The main reason for adopting this ktype of organisation is linked with the very different epistemological status of concepts which define a hgeneric, abstract mould for some useful notions to be taken into consideration in a given domain with orespect to the individuals, which represent specific entities occurring in the context of some concrete events nof the domain. In this respect, concepts are permanent, at least in the context of a given application ; indilviduals represent, on the contrary, unpredictable, randomly-occurring entities stored sequentially into the msystem according to their order of arrival in its environment. Please note that, see before, individuals are oalso linked with the concept hierarchy, where they appear as the leaves of particular sortal concepts ; they E?are, therefore, indexed by the H_CLASS hierarchical structure. Ce !D%jThe events proper to a given domain i.e., the dynamic processes describing the interactions among the kconcepts and individuals that play a role in the contest of these events are represented by making use E+of the descriptive and factual tools. Ee !F%hThe descriptive component concerns the tools used to produce the formal representations (called predicaltive templates) of general classes of narrative events, like moving a generic object, formulate a need, hhaving a negative attitude towards someone, be present somewhere. In the context of the descriptive mcomponent, the events taken into consideration must be structured events, i.e., they must be characterised kby the explicit mention of an actor, an object, an instrument, etc. Correspondingly and in opposition to lthe binary data structures used for concepts and individuals predicative templates are characterised by a uthreefold format where the central piece is a semantic  predicate , i.e., a named relation that exists among EOone or more  arguments   introduced by means of  roles  : G3iael(P i   (R 1  a 1 ) (R 2  a 2 ) (R n  a n )) , HSc.%fsee the examples in subsection 3.1. Presently, the predicates pertain to the set {BEHAVE, EXIST, EXPE0  [RIENCE, MOVE, OWN, PRODUCE, RECEIVE}, and the roles to the set {SUBJ(ect), OBJ(ect), ^SOURCE, DEST(ination), MODAL(ity), TOPIC, CONTEXT}. Please note that, in NKRL, predicates and oroles express only some functional relationships strictly necessary for the full appraisal of the meaning to obe represented. In this sense, our roles, e.g., are more similar to the correlators of Ceccatos operational flinguistics, see (Ceccato 1967) where to each correlator corresponds a set of language-independent, kmental operations than to the (syntactically constrained) Jackendoffs thematic roles (Jackendoff 1990), fwhich are strongly influenced by the search for some form of optimal correspondence between the semanltic contents and the surface form these contents can assume in a particular natural language. Templates are fstructured into an inheritance hierarchy, H_TEMP(lates), which corresponds, therefore, to a taxonomy E(ontology) of events. Ie AJ%iThe instances (predicative occurrences) of the predicative templates, i.e., the NKRL representation of HHˆ:BHHˆ?GCC ld:GG HHˆ:EHHˆ€OY::GJScSgsingle, specific events like Tomorrow, I will move the wardrobe, Lucy was looking for a taxi, Mr. 0ikSmith has fired Mr. Brown, Peter lives in Paris are in the domain of the factual component. The reasons jfor distinguishing between descriptive and factual component are identical to those already examined in a E#definitional/enumerative context . Ke Lu¾e1.2The upper layer  MScOe 1NZ| %iThe upper layer of NKRL consists of two parts. The first is a catalogue which gives a complete descripition of the formal characteristics and the modalities of use of the well-formed, basic templates (like hmoving a generic object mentioned above) associated with the language. Presently, the basic templates jare more than 150, pertaining mainly to a (very general) socio-economico-political context where the main lcharacters are human beings or social bodies. By means of proper specialisation operations it is then possimble to obtain from the basic templates the (specific) derived templates that could be concretely needed to kimplement a particular, practical application e.g., move an industrial process and the corresponding joccurrences e.g., move, in a well-defined spatio-temporal framework, this particular industrial producmtion. In NKRL, the set of legal, basic templates included in the catalogue can be considered, at least in a pfirst approach, as fixed (see the Conclusion for the advantages of this solution). Please note, however, that kthe possibility (if need be) of inserting new basic elements in the catalogue is not excluded, and new temEEplates can (carefully) be created on the model of the existing ones. Oe !P%hThe second part of the upper layer is given by the general concepts that pertain to the upper levels of H_CLASS such as  sortal_concepts ,  non_sortal_concepts ,  physical_entity ,  modality_ ,  event_ , etc., see jalso Figure 5 below. They are, as the upper levels of H_TEMP, invariable, i.e., they are not subjected to kchange when another application in a different domain is taken into account. These concepts form a sort of cupper-level, invariable ontology to be compared with Batemans Generalized Upper Model (Bateman, nMagnini and Fabris 1995), even if our selection criteria are, once again, functional more than linguistically E motivated. Qe Ru?e/2Examples of characteristic NKRL features SScJe TuVte#2.1Descriptive/factual components UScgme 1VrT%hFigure 1 supplies a simple example of factual NKRL code. It translates a fragment of fictitious, COBALT-flike news story : Yesterday, the spokesman said in a newspaper interview that his company has bought ithree factories abroad, which is represented according to the rules for encoding plural situations in ENKRL, see (Zarri 1997). We !X%hTwo occurrences (factual component), identified by the symbolic labels c1 and c2 and instances of basic ^NKRL templates, bring out the main characteristics of the event. The arguments human_being_1, gcompany_1, newspaper_1, interview_1, purchase_1, factory_99, abroad_ are individuals ; yesterday_ is a pfictitious individual introduced here, for simplicitys sake, in place of real or approximate dates, see, e.g., q(Zarri 1992) for some details about the representation of temporal information in NKRL.  spokesman_  and 1tcardinality_ , that pertain both to the  property_  subtree of the H_CLASS hierarchy, are concepts. The jattributive operator, SPECIF(ication), is one of the NKRL operators used to build up structured arguments  (or expansions), see (Zarri and Gilardoni 1996) ; the SPECIF lists, with syntax (SPECIF e 1  p 1   p n ), are Luused to represent some of the properties which can be asserted about the first element e 1 , concept or indicvidual, of the list, e.g.,  human_being  and  chairman_  in c1. The arguments, and the templates / occurrences 0_kas a whole, may be characterised by the presence of particular codes, determiners or attributes, which mgive further details about their significant aspects. For example, the location attributes, represented as EPlists, are linked with the arguments by using the colon (:) operator, see c2. Ye Z7vED %Uc1)MOVESUBJ(SPECIF human_being_1  (SPECIF  spokesman_  N??Ecompany_1)) OBJ#c2 [eDESTnewspaper_1 \eMODALinterview_1 ]edate-1:yesterday_ ^e date-2: __Sc}Ge HHˆ:EHHˆDJFF ld:JJ HHˆ:HHHˆ€>>J`7vEvEec2)PRODUCESUBJcompany_1 awe:OBJ(SPECIF purchase_1  (SPECIF factory_99 beE (SPECIF  cardinality_   3))): (abroad_) cSc|e d7vEV@e[ factory_99 ereInstanceOf: factory_ feHasMember:3 ] gScJ\e hPje&Figure 1 - An example of NKRL code. iSc\"e 1jg %hThe non-empty HasMember slot in the data structure explicitly associated with the individual factory_99 |makes it clear that this last, mentioned in c2, is referring in reality to several instances of  factory_ . Individmuals like factory_99 are collections rather then sets, given that the extensionality axiom (two sets are bequal iff they have the same elements) does not hold here. In our framework, two collections, say jfactory_99 and factory_100, can be co-extensional, i.e., they can include exactly the same elements, withhout being necessarily considered as identical if created at different moments in time in the context of ktotally different events, see also (Franconi 1993). In Figure 1, we have supposed that the three factories {were,  a priori , not sufficiently important in the context of the news story to justify their explicit representartion as specific individuals, e.g., factory_1, factory_2, factory_3 ; please note that, if not expressly required kby the characteristics of the application, a basic NKRL principle suggests that we should try to avoid any E*unnecessary proliferation of individuals. ke !l%jGoing on now with some information about the descriptive/factual structures, we reproduce in Figure 2 the i(tripartite), basic template of H_TEMP that gives rise to the occurrence c2 of Figure 1. In this figure, koptional elements are in round brackets (see, e.g., the role SOURCE which introduces the possible origin yof the situation). In the corresponding occurrences, see c2, the variables ( x, y, u,  etc.) are replaced by conlcepts or individuals according to the associated constraints, expressed as combinations of concepts pertainE!ing to the H_CLASS upper levels. me n7vE5e { PRODUCE3.1 ; acquire, buy oSc@8e p7vEIe/IsA : PRODUCE3 ; perform a task or action qScTJe r7vE^$&e7PRODUCESUBJ x  : [< location_ >] sgwXehOBJ(SPECIF  y e  | {  e  }+) (SOURCE u  : [< location_ >]) te3(DEST v  : [< location_ >]) ue(MODAL w ve(CONTEXT z ) we({modulators}) xeG[date-1: < date_ >, initial date | observed date] ye-[date-2: < date_ >, final date] zSce {8vEe2x =< human_being_or_social_body > |Meay  =< purchase_ > ;  e   =   < valuable_entity > }e7u  =< human_being_or_social_body > ~e2v =< human_being_or_social_body > eZw  =< modality_ > | symbolic label of predica tive occurrence e,z =< situation_framework >} %Fe)Figure 2 - An example of basic template. Sce qR %`Figure 3 is a schematic representation of the H_TEMP hierarchy, where only the branches BEHAVE, aMOVE and PRODUCE have been developed to some, very limited extent. In this figure, the syntactic odescription of the templates is particularly sketchy : e.g., all the symbolic labels have been eliminated, and ithe templates are discriminated only through the associated natural language comments. For a more realisitic picture of a template, see Figure 2 above. The codes ! and _ mean, respectively, mandatory and jforbidden (e.g., in the transmit an information to someone template, MOVE sub hierarchy, the presence lof a DEST(ination) role is expressly required). We can conclude the discussion of Figure 1 by noticing that jthe MOVE construction at the origin of c1 is necessarily used to translate any event concerning the transdmission of an information (the spokesman said ). The corresponding template makes use of what is ocalled a completive construction. Accordingly, the filler of the OBJ(ect) slot in the occurrences (here, c1) kwhich instantiates the transmission template is always a symbolic label (#c2) which refers to another predlicative occurrence, i.e., the occurrence bearing the information content to be spread out (the company has HHˆ:HHHˆGMII ld:MM HHˆ:KHHˆ̬MScSE6bought three factories abroad ), see also Figure 3. ie !%hAs a second example of descriptive/factual structures, we give now, Figure 4, an NKRL interpretation of fthe narrative sentence : We have to make orange juice which, according to Hwang and Schubert (Hwang gand Schubert 1993: 1298), exemplifies several interesting semantic phenomena. To translate the general E=idea of acting in order to obtain a given result, we use : e #:%gi) A (predicative) occurrence (c3 in Figure 4), instance of a basic template pertaining to the BEHAVE fbranch of H_TEMP, and corresponding to the general meaning of focusing on a result. This occurrence ois used to express the acting component, i.e., it allows us to identify the SUBJ of the action, the temporal EHco-ordinates, possibly the MODAL(ity) or the instigator (SOURCE), etc. !z+~e  :Sci%fii)A second predicative occurrence, c4 in Figure 4, which contains a different NKRL predicate (e.g., 0P_PRODUCE in Figure 4) and which is used to express the intended result component. Please note ethat, for all the focus on constructions, the reference time is the timestamp (observed date in bFigure 4) linked with the first occurrence (BEHAVE). The second occurrence, which happens in the gfuture, is necessarily marked as hypothetical, i.e., it is always characterised by the presence of an E,uncertainty validity attribute, code *.  !z+!.e  :Sc%iiii)A binding occurrence, c5, linking together the previous predicative occurrences and labelled with p߶kcGOAL, an operator pertaining to the taxonomy of causality of NKRL. Binding structures, templates aor occurrences i.e., lists where the elements are symbolic labels, c3 and c4 in Figure 4 are esecond-order structures used to represent the logico-semantic links which can exist between (predicaE!tive) templates or occurrences. HHˆ:KHHˆJPLL ld:PP HHˆ:NHHˆ‚h??P "vEvEe2H_TEMP  (hierarchy of predicative templates)  Scօe 9vEe3.. BEHAVE templates  ; predicate : BEHAVE Sce 9vEse;...  external manifestation of the subject ; _OBJ <ee.... acting in a particular role ; MODAL <  role_  [ex:  rugby_player ] > eM.... manifest a particular quality ; MODAL <  quality_  > ScQe 9vE[nel...  focus on a result ; _ OBJ, DEST, TOPIC ; _modulator against, for ; !GOAL binding structure eeT.... act explicitly to obtain the result   ; _modulator ment e:.... wishes and intentions ; ! modulator ment e   ef...  concrete attitude toward someone/something ; !OBJ, MODAL ; _DEST, GOAL ; _mod. ment Scvve 9vEOe].. EXIST templates  ;   predicate : EXIST ; !location of the SUBJ ; _DEST Sc e 9vEdeN.. EXPERIENCE templates  ; predicate : EXPERIENCE ; !OBJ ; _DEST Sce 9vEe/.. MOVE templates  ; predicate : MOVE Sc#;e  9vEe@...  moving a generic entity ; OBJ <  entity_ > !OeI.... move a material thing ; OBJ <  physical_entity  > "eT..... change the position of something ; _DEST (ex: move the wardrobe) #eT..... transfer something to someone ; !DEST (ex: send a letter to Lucy) $ScVhe %9vE/ej...  generic person displacement ; SUBJ = OBJ = < human_being > ; !location of SUBJ, OBJ &Sc e '9vEiVe9...  transmit an information to someone ; !DEST (eo.... transmit a generic information ; OBJ <  type_of_information  [ex:  message_ ] > )e_.... transmit a structured information ; OBJ label of binding/predicative occurrence *Sc3oe +9vE=IQeA.. OWN templates   ; predicate : OWN ; !OBJ ; _DEST ,ScGe -9vEQe=.. PRODUCE templates  ; predicate : PRODUCE ; !OBJ .Sc[(e /9vEee9...  conceive a plan or idea ; !modulator ment 0Scpe 19vEyea...  creation of material things ; OBJ <  physical_entity  > ; _modulator ment 2ScVVe 39vE/eH...  perform a task or action ; OBJ <  action_name  > 4e:.... acquire, buy ; OBJ <  purchase_  > 5e-.... sell ; OBJ <  sale_  > 6Sc6Qe 79vEes...  relation involvement ; SUBJ (COORD) ; OBJ  mutual_agreement  MODAL < relationship_ > 8Scoe 99vEI?et...  production of events by an active cause ; SUBJ <  active_cause  > ; OBJ <  event_ > :7Ҝqe ;9eH.. RECEIVE templates   ; predicate : RECEIVE ; !OBJ ; _DEST <ScOe =%ؖe
ScOe ?!z+ le @ke A%evThe general schema for representing the focusing on an intended result domain in NKRL, see also Figure 3, is then : BSc)6Be C=z#3me/c a )BEHAVESUBJ< human_being_or D?+?fe_social_body > E=#IfeBc b )* , with any syntax FU^ke1c g )(GOAL c a  c b ) GScbe H=z+l=%zIn Figure 4, oblig and ment are modulators, see (Zarri 1995), i.e., particular determiners used to refine or modify pv=tthe primary interpretation of a template or occurrence as given by the basic predicate roles argument associaution. Ment(al) pertains to the modality modulators. Oblig(atory) suggests that someone is obliged to do or to HHˆ:NHHˆMSOO ld:SS HHˆ:QHHˆ„<<SH=z+zvendure something, e.g., by authority, and pertains to the deontic modulators series. Other modulators are the tem0y rporal modulators, begin, end, obs(erve), see again (Zarri 1992). Modulators work as global operators which wtake as their argument the whole (predicative) template or occurrence. When a list of modulators is present, as in the voccurrence c3 of Figure 4, they apply successively to the template/occurrence in a polish notation style to avoid any spossibility of scope ambiguity. In the constructions for expressing focus on , see Figure 3, the absence of the lment(al) modulator in the BEHAVE occurrence means that the SUBJ(ect) of BEHAVE takes some concrete initiative (acts explicitly) in order to fulfil the result ; if ment is present, as in Figure 4, no concrete action is undertaken, and the result reflects only the wishes and desires of the SUBJ(ect).  several_ , see c3 and c4, is used conventionally yin NKRL to represent the cardinality of sets of totally undefined size, like those corresponding to a generic plural refverent, as in men or books, see (Zarri and Gilardoni 1996). In c4, i is conventionally used to denote an unknown EFtime increment with respect to the timestamp that characterises c3. IScuHe Jie K7vECe&c3)BEHAVESUBJ(SPECIF informant_1 L6%O  human_being    (SPECIF  cardinality_  8Eseveral_ )) M7e [oblig, ment] Ne date1: observed date Oe  date2: PScC>e Q7vEeHc4)* PRODUCESUBJ(SPECIF informant_1   human_being  RoeD (SPECIF  cardinality_    several_ ))) !S%` OBJ(SPECIF  orange_juice   (SPECIF  amount_ )) Edate1: observed date + i Te date2: UScɝe V7vEec5)(GOAL c3 c4) WSc4e X%e6Figure 4 - Representation of wishes and intentions. YSc%1e Zu0e-2.2Definitional/enumerative com-ponents [Sc;|e 1\Fbi%jFigure 5 gives a very sketchy representation of the upper level of H_CLASS (hierarchy of concepts, definistional component). Note, in this figure, the presence of a sortal concept  event_ . As already stated, the qevents represented by means of templates and occurrences must be  structured events , i.e., they must be ocharacterised by the specific indication of an actor, an object, etc. If we only want to explicitly mention an wevent (e.g., president_clinton_interview_49),   without giving all its structural details, we will simply make c() use of a particular individual, i.e., of an instance of  event_ .  substance_  and  colour_  are regarded as exam0~ples of non sortal concepts. For their generic terms,  pseudo_sortal_concepts  and  characterising_concepts , EOwe have adopted again the terminology of (Guarino, Carrara and Giaretta 1994). ]e !^%hThe data structures used for concepts and individuals are essentially frame-based structures, and their mdesign is relatively traditional. These structures are composed of an OID (the generic symbolic label of the mconcept to be defined, or the specific name of the individual to be created), and of a set of characteristic sfeatures (slots). Three different types of slots are used, relations, attributes, and procedures, see, e.g., E,(Zarri 1995a, Zarri 1997) for some details. _ue03A detailed example of NKRL representation `Sc$%fConsider the following section of the Maria Otero's text titled Latin America : Accion Speaks Louder  E:then Words and proposed for the Interlinguas Workshop : ae !b %hBanco Solidario, S.A., or Bancosol, grew out of a non-profit joint venture created in 1986 by prominent ]members of the Bolivian business community and ACCION International. The latter brought with `them leadership and seed capital, while the former provided technology and methodology. PRODEM, aas the programme was named, provided credit and training to broaden employment opportunities for bthe very poor self-employed, encourage investment in microbusiness, and increase the income generbated by this sector. PRODEM used the group lending technique of solidarity groups and began makeing small working capital loans. In its first five years of operation, PRODEM financed loans to over `13,300 microentrepreneurs, 77 per cent of whom were women, disbursing over $27 million in loans Eaveraging $273 Ace HHˆ:QHHˆPVRR ld:VV HHˆ:THHˆ..@@VdScSe!Two general remarks apply here : e!z+e fSci%l All the occurrences of the translation are instances of standard basic templates pertaining to the :PEaNKRL catalogue, see above. No new template has been created specially for the purpose in hand. g!z+e hSc6%i The concepts (and their instances) used in the translation are, in their great majority, standard :G_H_CLASS concepts, common to many possible applications. A few  ad hoc  concepts, like @qgroup_lending_technique  or  working_capital  have been created, however, to keep the translation as ":cmuch as simple and comprehensible as possible. Note that, as already remarked above, when the argudments of the semantic predicates represent general properties, or when there is no precise need for hcreating specific individuals to be used again, e.g., in other occurrences (coreference), the arguments E=are represented as generic concepts instead of individuals. ie jc'ks m  k%6&e>Figure 5 - An abridged view of the upper level of H_CLASS . lScGkpe m*2-uTe NKRL coding nSc^e o7vEhe1)(REFER 2 3) pScs3[e 1q~%gThe coding of the textual fragment examined includes two main elements : the creation of Bancosol from qthe PRODEM non-profit joint venture ( 2 ), and the description of the characteristics and aims of PRODEM  ( 3 ).  REFER  is the NKRL operator used to represent a weak causality relationship :  3  is necessary, but not E=sufficient, to explain  2 , see, e.g., (Zarri 1992). re s7vEe$2)EXISTSUBJbancosol_: (bolivia_) te!SOURCE(SPECIF prodem_ (SPECIF ue+  joint_venture non_profit )) ve[abs, begin] wedate-1:1992 xe date-2: ySce z72-"$%lEXIST + [abs, begin]  is the NKRL formula (template) used to express the origin (the birth) of living  Ebeings or social bodies. {Sc e |7vE9e3)(COORD 4 5 6) }Sc#Fye 1~.,%The description of PRODEM's characteristics concerns the details of its creation ( 4 ), the aims ( 5 ), and the E@description of the first five years of operation ( 6 ). e 7vEMe4)(COORD 7 8 9) ScX3?e 7vEb %Q7)PRODUCESUBJ(COORD1 (SPECIF busi- nessman_1  bolivian_  8k_limportant_  (SPECIF   cardinality_ several_ ))  accion_international):  7E (bolivia_) AeKOBJ(SPECIF prodem_ (SPECIF   joint_venture non_profit )) HHˆ:THHˆSYUU ld:YY HHˆ:WHHˆ„AAY 7vEvEedate-1:1986 we date-2: Sc)e e 7vEs%]8)MOVESUBJ(SPECIF businessman_1  boliv- ian_ important_  (SPECIF  8<Ecardinality_ several_ ))  7e6OBJ(COORD1  technology_ method- ology_  eDESTprodem_  edate-1:1986  e date-2:  Scge reJThe Bolivian businessmen provided PRODEM with technology and methodology. e 7vEe"9)MOVESUBJaccor_international e@OBJ(COORD1  leadership_ ini- tial_capital ) eDESTprodem_ edate-1:1986 e date-2: Sc<e 7vE-e5)(COORD 10 11) Scvme 1\%rPRODEM's aim was to provide credit and training for the very poor self-employed etc. ( 10 ) ; to do this, E:PRODEM used the group lending technique ( 11 ). e 7vEe&10)(GOAL 12 *(COORD 13 14 15)) Scc3e 1 I%|The provision of credit and training ( 12 ) was intended to broaden the employment opportunities ( 13 ), to EPencourage investment ( 13 ), and to increase the income ( 14 ). e 7vE*e12)MOVESUBJprodem_ 4Be,OBJ(COORD1  credit_ training_ )  e DEST(SPECIF self_employed_1 !e& (SPECIF  poor_ very_ ) "e: (SPECIF  cardinality_ sev- eral_ )) #edate-1:after-1986 $e date-2: %ScmC%e &x)e '7vE%F13) EXPERIENCESUBJ(SPECIF  self_employed_1  (SPECIF 8VELpoor_ very_ )  (SPECIF  cardinality_  several_ )) (7e3OBJ(SPECIF  employ- ment_opportunity )8e greater_ ) *7edate-1: after-1986 +e date-2: ,Sce 1-%lThe EXPERIENCE templates are typically used to translate the fact of being in a given state, be affected E$b y positive/negative events, etc. .e /7vE叡e14) BEHAVESUBJprodem_ 0e>OBJ(SPECIF  investment_ mi- crobusiness_ ) 1eMODAL moral_support 2e[for] 3edate-1:after-1986 4e date-2: 5Sce 16)v@%iThe above NKRL structure is typically used to express a concrete, favourable attitude to someone or someE thing, see also Figure 3 above. 7e 87vEIae15) PRODUCESUBJprodem_ 9Ro%LOBJ(SPECIF   expansion_   (SPECIF  income_ mi- 8Ecrobusiness_ ) :7edate-1:after-1986 ;e date-2: <Scxie _=7vE‚e11)(COORD 16 17) HHˆ:WHHˆV\XX ld:\\ HHˆ:ZHHˆ>>\ >ScSe ?ienTo fulfil its aims, PRODEM used a group technique ( 16 ) and began making small loans ( 17 ). @e A7vE)te16) BEHAVESUBJprodem_ B|%XMODAL(SPECIF   user_  (SPECIF   group_lending_technique  8E!solidarity_groups ))   C7edate-1:after-1986 De date-2: EScV|e 1Fa%jThe BEHAVE template corresponding to this occurrence is used to represent the idea of acting in a parESticular role (here, role   =  user_  ), see again Figure 3 above. Ge H7vEce17) PRODUCESUBJprodem_ I4%kOBJ(SPECIF   loan_   work- ing_capital small_  (SPECIF  cardi- nality_ 8Eseveral_ )) J7e[begin]   Kedate-1:after-1986 Le date-2: MScc<e NIe O7vE"e6) PRODUCESUBJprodem_ 1Pv*%tOBJ(SPECIF    loan_1  dollar_usa    (SPECIF  cardinality_ sev- eral_ ) :(SPECIF   global_amount  (SPECIF  8Emillion_27 )) (SPECIF Q7e'  average_amount  (SPECIF Re  unit_  273))) !S%PDEST(SPECIF microentre- preneur_1 (SPECIF  cardi- nality_ Q(SPECIF  more_than   13,300)) (SPECIF  subset_   Mmicroentrepreneur_1  (SPECIF  cardinality_   (SPECIF 8EDpercent_  77 micro entrepreneur_1))  female_ )) T7edate-1:1986 Uedate-2:1991 VSc@^e WJeQThe DEST(ination) role is sometimes called benefactive role in the literature. Xe Yuabe Conclusion ZScl[e 1[wB`%dSeveral (at least partly) implemented formalisms exist that claim to be able to represent extensive ]chunks of natural language semantics see Conceptual Graphs (Sowa 1984), SNePS (Shapiro and ]Rapaport 1992), CYC (Lenat and Guha 1990), LILOG (Herzog and Rollinger 1991), Episodic Logic b(Hwang and Schubert 1993), etc. Moreover, since Schanks work (Schank 1973), several authors have ktackled the specific problem of representing structured events see, e.g., the recent Parks proposal (Park Eg1995), where a set of primitives for modelling the dynamic aspects (events) of a domain is provided. \e !]%dIn defence of the introduction of the NKRL formalism, we can however put forward (at least) the two Efollowing arguments : ^e _!%f Making use of a relatively simple, intuitive and easily manageable formalism, NKRL offers some ":kinteresting solutions to very hard problems concerning the practical aspects of the knowledge representaetion endeavour, like modalities, temporal representation, representation of the wishes and intention ERdomain, completive constructions, coding of second order logical structures, etc. `!z+- e aSc%h A fundamental (and apparently unique) characteristic of NKRL is represented by the fact that the 2:$Jmcatalogue of basic templates, see subsection 3.1 above and Figure 3, can be considered as part and parcel of kthe definition of the language. This approach is particularly important for practical applications, and it mimplies, in particular, that : i) a system-builder does not have to create himself the structural knowledge Eneeded to describe be #c%nthe events proper to a (sufficiently) large class of narrative texts and documents ; ii) it becomes easier to Ewe W# I2e HHˆ:]HHˆ\^^ l}H=1aH EGeH* }6=`b6 EG eN }-=ac- EG eN }?=b,? EG e }=+e FG e P:Biblio }H=dfH FG eP }6=eg6 FGeN }-=fh- FGeN }?=g1? 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