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<Paper uid="J79-1082">
  <Title>American Journal of Computational Linguistics Microfiche 82 A MODEL FOR KNOWLEDGE AND ITS APPLICATION TO DISCOURSE ANALYSIS</Title>
  <Section position="2" start_page="72" end_page="72" type="abstr">
    <SectionTitle>
INTKODUCTTON
</SectionTitle>
    <Paragraph position="0"> An important csntribution of natural Language processing has been to direct a ttr:n tion to tile structure of 1~~1gi~age at the discau~.se I I level, wl-rich hna led r6 n greater awareness uE the rote of meaning&amp;quot; in Iangtxage For &amp;quot;A text is best: regarded as n SEIAhTXG unit; a unit not aPS form but of meaningt' (Ilalliday ct Ilasan, 1976, p. 2). This being so, discsursc analysis will deepen ur tlndcrstanding sf meaning and vice-versa In this paper 1: present a rnodel, of nzcaning stran~ly inf'l~lencccl hy Ilays (].969a, 3.969b, 1970, 1973) and stlow hob I t; is able to ccciptwre tf~c otganizattnn of L!~HCDU~SC~. In particular T seek to define the organization of cahercnt di~courst-. and to slaow llow knowledge is u'sed to inhex a coherent structure when, as usually is the case, the surface forrr: is ell f~3tic. Tt~e hypathescs arc a~sed to buiLd an automati-c system tcn test the coherence of d ibscnnrsc.</Paragraph>
    <Paragraph position="1"> A f hO'fJR1, FOl&lt; IiiJCIE.JX,l? DCJ; The pl~ilosopf~ic stnr~cc -fs taken that utrr knowlr.dg.,c of ;I csncep is the f~icarling of ct~at concept: : &amp;quot;5arrtcanc wt~o knows wi:at tik-t.r means . . Is required to know that w~ercntyp~tal tigers are striped&amp;quot; (Futnanr, 1975, p 249) 1 )!any models of kr,owX.edfie 'have bccn d&lt;welopeb for use In computatioraal env-dr:,nmcnts .. Samp arc. fc~ nrcstr ic tt.d dl-~mrai.rrz; (Black, 1908: Ebbrow, 1968; Colby, 1973; Raphael, 1968; Winograd, 1W1; etc.) The present model is raore'in the tradition of Klein, Oakley, Suurballe, and Ziesemer (1 972), Quillian (1 969), Rumelhar t , Lindsay, and Normaa (1972), Schank (1975ai, Shapiro (1971), Simmons (1970), and Wllks (1972), where no particular context is prescrfbed* It will be apparent that at many points the present model draws upon these earlier syatems. Some of the differences between systems are probably differences in notation- However no system Is at a stage of co~staney or completeness that makes it worthwhile to devote much effort to establishing the equivalences Although it wauld be possib1.e to present only the paws that I believe to be novel, giving the whole system in a common notation will ease the task of the reader-The model, hereafter called the encyclopedia, endeavors to be consistent with available psychological and linguistic views of the structure of language and t'hought, for any automated language system must closely imitate the ttorkings of human cognition to be successful (Collins &amp; Quillfan, 1972).</Paragraph>
    <Paragraph position="2"> The encyclopedia encodes common knowledge sf the world which may differ from scientifically accurate descriptions. Putnam (1975) calls such knowledge &amp;quot;stereotypical&amp;quot;: The fact that a feature . . . le, included in the stereotype associated with a word X does not mean that it is an analytic truth that all Xs have that feature, nor that most Xtl have that feature, nor that all normal Xs have that feature, nor that some Xs have that feature. . . Dtwovering that our stereotype is based on nonnormal or unrepresentative members of a natural. kind is not discovering a logical contradiction. a . [but) The fact is that we could hardly communicate if moat of our stereotypes weren't pretty accurate as far as they goe (pp. 250-251) The encyclopedia is achematized and ihplemented as a directed graph; in current parlance it is a network model. Nodes characterize concepts and arcs relations between conceptsv The most general statement to make about the model is that relations and aoneept types are the necessary system primitives; some concepts may be primitive, but the model does not depend on the* existence of primitive concepts Discussion wi2 1 cover the nodes and relations of the model.</Paragraph>
    <Paragraph position="3"> Attention will also be given to network processes.</Paragraph>
    <Paragraph position="4"> No psychol~gical validity is claimed for the content of any of the structures shown; the claim extends only to the relational sttucture Questions of content must be answered empirically-</Paragraph>
    <Section position="1" start_page="72" end_page="72" type="sub_section">
      <SectionTitle>
Nodes
</SectionTitle>
      <Paragraph position="0"> There are four types o.f nodes: -9 event Yr entit .-- attribute, and modality. The first three correspond to simple verb simple noun, and simple modifier, respectively. The fourth type of node is novel Its rale in *he system will become clear after a description of arcs * For the meantime it will, have to suffice to say that it is used in the spatio-temporal causal, belief, and hiersrchic organization of knowledge * Its ancestor in linguistic theory is &amp;quot;modal&amp;quot; in the model/proposition dichotomy of Fillmore (1969). Sch~bert (1976) has predicate nodes that are similar in motivation, but different in use from modality nodes.</Paragraph>
      <Paragraph position="2"> Nodes of the encyclopedia are not labeled (Collins &amp; Quillian, 1972). An arc, termed - name, points from a node into a dictionary of print names. For clarity nodes in diagrams will be annotated, but this should not be taken as representing the implementation, which is as shown in Figure 1.</Paragraph>
      <Paragraph position="3">  In all the following figures is an event, entity or attribute node- Annotations on these nodes are enclosed in 1, &lt;&gt;, and [I, respectively- Modality nodes appear as o and are never annotated.</Paragraph>
    </Section>
    <Section position="2" start_page="72" end_page="72" type="sub_section">
      <SectionTitle>
Arcs
Five
</SectionTitle>
      <Paragraph position="0"> types of arcs are used in the network: paradigmatic arcs ate taxonomic, syntagmatic arcs iorm propositions, discursive arcs link propositions, the rnetalingual arc is used to associate a concept with a story in network form that defines the concept, and status arcs characterize beliefs and desires +</Paragraph>
    </Section>
    <Section position="3" start_page="72" end_page="72" type="sub_section">
      <SectionTitle>
Paradigmatic Relations
</SectionTitle>
      <Paragraph position="0"> Variety. A readily observable aspect of human behavior is the existence of folk taxo~~omies. These have been studied in detail by ett~nasemantlcist s in order to discover their cogniti~e significance and structure: Man is by nature a classifying animal. His continued existence depends on his ability to recognize similarities and differences between objects and events in Iris physical universe and to make known these similar ities and differences linguistically . Ifideed , the very development of the human mind seems to have been closely related to the perception of discontinuities in nature. In view of this, the study of folk taxonomic systems, which have received a great deal of interest in recent years, has a high significance in interpreting the logical processes going on in our minds, as well as in understanding the application and utility of the taxoncmfc systcms themselves. (Raven, Eerlin, 6 Breedlove, 1971, p 8 1210) For example, mammal, bird, and reptile might be classified as kinds of vertebrates* Tn the network, the relation is termed variety (abbreviated to VAR in the figures), Figure 2 diagrams this knowledge.  Varietal nodes are seen as representing concepts at a categqrical level, hence variety is the category-subcategory relation. Berlin, Breedlove, and Raven (1968) show the existence of covert categories in folk taxonomies, Lee, nodes having scientific, but not folk, names, It say vertebrate&amp;quot; in Figure 2. These categories are revealed by memory, classification, and other experiments. ThLs is counter to the view of Conklin (1962) for whom concepts must have monolexemic labels. Covert categories enable Raven et ale (1971) to show a degree of uniformity in taxonomies: about five hierarchic levels with seldom more than five hundred items under one node. Berldn et al. (1968) claim that items in a folk taxonomy form non-intersecting categories+ i .e., the structure is strictly tree-like. This view is not held here, for a typewriter can be classified both as a machine and as a writing instrument. Cobequently , varietal structures are not restricted to being treelike. Loops, however, do not seem possible. Nor is it necessary that A n~de have a name.</Paragraph>
      <Paragraph position="1"> Enstance. kogic since Aristotle has distinguished between category (or type) and a specifk member of a category (token). This membership relation is termed instance (IST). For example, &amp;quot;William Proxmire&amp;quot; is an instance of &amp;quot;person&amp;quot;, Figure 2. Most instances are not named, takhg their name from their varietal parent, but a major exception is people, ebg., &amp;quot;~eter&amp;quot;, &amp;quot;Aunt Sally&amp;quot;, Figure 1. Any path through the paradigmatic organization of knowledge which follows only arcs having the same dixectionality (termed a paradigmatic path) contains at most one instance arc. Traversing this arc represents a cognitive transition from thinking about categorical concepts to thinking about particular concepts, e .g . , from thinking about man to thinking about Abraham Lincoln, or from blueness to the blue of your car.</Paragraph>
      <Paragraph position="2"> Rumelhart st al. (1972) use an ISA relatidn that cover8 both variety and gnstance, e.8~~ ISA(Luigi s ,tavern) and ISA(tavern,establishment). The present feeling is that a distinction does exist ; hence the two relations of the encyclopedia Typical. A third condition of knowledge needs to be represented.</Paragraph>
      <Paragraph position="3"> Concepts have both universal and occasional properties. For example, &amp;quot;birds eat wormst' is an occasional, not universal, fact about birds as some never do, but bven those that do are sometlmeg Iound eating fruit, fish, or even not eating, withbut the proposition being necessarily false However, &amp;quot;birds have wings'' is expected to be true at all times for all birds; it is a pathological situation if a counter-example is f oubd. To represept te arguments of occas2onal predications, the Dical (TYP) arc is used. Thus the &amp;quot;blrd&amp;quot; in &amp;quot;bfrds eat worms&amp;quot; is as in Figure 2. It is also possible to use the typical relation to attach occasional proper ties to members of categories, i .e., to instances. In Figure 2 is show the represenation of &amp;quot;William Promire makes foreign policy statements&amp;quot; where this is a statement of an occasional habit rather than a record a specific act. No positlon is taken on how noteworthy knowledge ie recognized as such in the development of the encyclopedia Manifestation. The final paradigmatic relation is manif es-t-ation (MAN) This corresponds to- the phenomenon of object constancy: An object may undergo change in space and time, but it is still perceived as the same objee t. For -ampla, William Proxmire before apd after his hair transplant is still William Proxmire. Also an object may participate in many different actions but still preserve its identity, e.g., Albert Einstein playing a violin and Albert Einstein writing on a blackboard remains Albert Einstefn = TI the system each diffetefii situatj.9~ involves a distinct node. To a node defined by an instance are linked, by manifestation arcs, nodes that correspond to an object in its different guises Manifestations of &amp;quot;William Proxmirett are shq~ln in Figure 2. bnifestations do not ustPally have names different from that of their pareat instance; g rare exception tp this is the Evening Star and the Morning Star which are both Venus at different times of the day.</Paragraph>
      <Paragraph position="4"> Maalfestatians of varietal and typical concepts are also possible.</Paragraph>
      <Paragraph position="5"> The latter are used for pro~erties that are true of the concept but only at spme point or period of time, for example, &amp;quot;vertebrates are horn&amp;quot;, Figure 2. For typical arcs this notion is redundant as typical embodies spatial and temporal inde tgrminancy . However manifestation does have a use with the typical arc in representirrg ~oreference.</Paragraph>
      <Paragraph position="6"> Suppose it can happen that a person can trip causing him to be hurt. The Uperaon&amp;quot; in the encoded event is a typicalised &amp;quot;person&amp;quot;, but it must be the same person that trips that is hurt. Figure 2 shows the use of manifestation relations to indicate this identity. More will be said later about the formal representation of the causal relation indicated in Figure 2. If only typical arcs were used, the interpre~atian would b,e that anyone tripping could cause literally anyone to be hurt. Multiple manifestations can also be used with variety if coreference needs to be marked.</Paragraph>
      <Paragraph position="7"> [This next paragraph is almost certain not to make sense until the I I reader has completed as far as, and including, the section Tnheritance&amp;quot;, and so he may clloose to leave it and return later-Other systems, Quillian (1969), Rumelhart et al. (19721, and Schank (1975a), do not use manifestation but capture object constancy by having one and the same node for a participant in all of its propositions. This is a viable alternative. Nevertheless, information on the relative standing of the appearances of the participant has to be representable- If a single node were used in the encyclopedia, the differentiation could be made on the modality nodes of rile propositions. This route was not taken as it is more convenient, for example, to let the nature of the inherita'nce be determined completely in paradigmatic organization, rather than in a rnix ture of paradigmatic and discursive structures. For even without manifestation, the varietal structure will require the process of inheritadce.</Paragraph>
      <Paragraph position="8"> Of the four arcs, variety, typical, and manifestation can be iterated; instance cannot . Figure 2- and 3 illustrate iterative arrangements of variety and manifestation- That typical also has this property is seen from cofisidering that &amp;quot;While dreaming, some people talk or sleep-walk&amp;quot;. None ot these propositions are universally true, but only of arbitrary people. Figure 2 contains thie situation. The above examples present only paradigms of entities. but events and attributes also exhibit this kind of organization.</Paragraph>
      <Paragraph position="9"> If paradigmatic structure is a loopless directed graph then there will be origin nodes, that is, nodes without entering arcs. Can anything be said about the number or kinds of concepts associated with origin nodes? It is speculated that entities can be divided into doma-ins - of being each of which has its own paradigm. Possible domains are thing, soul, role, time, etc. Thus to represent Ford as President of the USA the structure in Figure 3 would be used. Figure 3 also shows how the totality of John brown (JB) and his fragments, as i~ &amp;quot;~ohn Brown's body 1 ies mouLdering in the grave but his soul goes 'marching on&amp;quot; can be represented .</Paragraph>
      <Paragraph position="10"> Figure 3 Domains of being To date scholars have only studied entity paradigms in detail* Little investigation of attribute or event paradigms has taken place. V It is hard to intuitively discern the hierarchical ordering of these concepts, i.e ., to know which concepts imply others. Red, yellow, etc., are obviously varieties of color, but does having mass imply having color?--but many gases and glass have mass but are colorlesso Or does having color imply having mass?--but red light, blue jokes, etc Or are they quite independent attributes that happen to have a large intersection in their domain of applicability? fiese are all open question8 in the taxonomy of attributes. The event paradigm is also open to much speculation.</Paragraph>
      <Paragraph position="11"> Syntagmatic Relation8  Syntagmatic relations connect nodes from different paradigms (with one exception). Relations of participation, similar td Fillmore s (1969) case relations, connect entities and events. A relation of mlicatioa (APL) link$ attributes *to events or to entities rn A relation of part-whole (P-W) c~nnects a unity to its component^. A syntagmatically related structure is termed a prpposlltion. Four relations of participation are distinguished: agent (AGT), instrumental (INS), objective (ORJ), and experiencer (EXP) . The role characterized by each is derived from dichotomies animate/inanimate and causal/non-carnal, as given in Table 1 (Fillmore, 1969).</Paragraph>
      <Paragraph position="12">  The set of case relatkbns does not include locative and temporal relations. Sentence adverb ials (Chobsky, 1965 ) are not part of SYntagmatic strucrare, but of the contextual structure, which fs here represented on modality nodes. Bound adverbial8 are part of syntagmatic structure, e.g., &amp;quot;ferociously&amp;quot; above, and are related to the event node by a relation of application.</Paragraph>
      <Paragraph position="13"> A part-whole relation is used in Figure 4 to show the relation of &amp;quot;handle&amp;quot; to &amp;quot;axe&amp;quot;. This relation differs from other eyntagmatic relations in that it connects nodes of the same type, emge, two entities.</Paragraph>
      <Paragraph position="14"> A case can be made for this relation to be considered a paradigmatic relation; for the present it has been put in with the syntagmatic mainly because it is not used by the process of inheritance, of which more later.</Paragraph>
    </Section>
    <Section position="4" start_page="72" end_page="72" type="sub_section">
      <SectionTitle>
Discursive RelatLons
</SectionTitle>
      <Paragraph position="0"> Propositions do not occur in isolation. They are tied together in cognition in a number of ways. The spatial, temporal, and causal connections are characterized by$iclcursive ares. Intuitively th~e are relations between whole propositions and it is to fail to capture this feeling if, say, a cause relation directly link8 two event nodes.</Paragraph>
      <Paragraph position="1"> Modality nodes are uaed to represent situations in Which the whole proposition la involved. Though schematically linked to an event node; conceptually the modality belonse to the whole propoeition.</Paragraph>
      <Paragraph position="2"> Discursive arca relate the modalities of propositions. Thus &amp;quot;Mary slapped John because he chased her&amp;quot; is represented as in Figure 5.</Paragraph>
      <Paragraph position="3"> Figure 5 Discursive organization</Paragraph>
      <Paragraph position="5"> The one causal relation, cswe, admits of no finer distinction. Others (Schank, 1975a; Halllday &amp; Haaan, 1975) distinguish three kinds ~f causation: reason, result, and purpose. The single cause relation of the encyclopedia models the first tw direcrly. Purpose (or enabling) causation is seen as separable into cauae together wf th a desire for the consequent. For example, a cup may fell causing it to break. The fall could be accidental or it could be deliberate with the purpose of breaking the cup . The same causal relation exists between the actions in both cases, but the analysis of the putposive situation will in-lve &amp;quot;desire&amp;quot;.</Paragraph>
      <Paragraph position="6"> Time arcs do permit subdivision. A proposition may be simultaneous (SML) with another proposition: &amp;quot;Fred washed the car while John chased Mary&amp;quot;, Figure 50 A sequenttal rn iering of propositions is also found, characterized by a sequence (SEQ) relation. The suggestions made here for the organization of space are only a working set for which little justification can be offered: location (LOC)--a neutral statement of position, contact--in physical contact, and -* near far above below left , etc., which are self-explanatoryo -# -9 -9 -* Figure 5 represents the location of &amp;quot;Fred washed the car&amp;quot; as being tt garage&amp;quot;. Since this work was completed Sondheimer (1977) has propaeed an analysis of space and the.</Paragraph>
      <Paragraph position="7"> The Me talingual Relation  Speech acts do not make use only of forms having physical reference,e.g., table, John, blue. A most important aspect of language behavior is abstraction- Human social, scientific , and intellectual development is dependent on the ability to create and control abstract concepts- A quick appraisal of thi9 paragraph reveals many such concepts: language, behavior, bocial, etc . A system that seriously hopes to approach human capabil ities must have a corresponding ability.</Paragraph>
      <Paragraph position="8"> One part of modeling abstraction 5s representation; but what is to be represen tedg AbsOrsc tion involves knowing a situation in which the nbst rac t term applies and replacing the sltu~tional description by the abstract term. An example is &amp;quot;tragedy&amp;quot;- The scene to which it is  applfcable is, say, Someone does a good act that: results in his death&amp;quot;. This definiens is encoded in rigure 6. &amp;quot;Tragedy&amp;quot; names a single node.</Paragraph>
      <Paragraph position="9"> Figure 6 Metalingual organization The general propositions of the definiens are conjoined using a modality node linked to the modalYties of the propositions by part-whole relations. In general there nay be any number of levels of modalities related by part-whole. To complete the association of the definiendum with its deftniens, a metallngual (PEL) arc links the former to the appropriate modality in the latter, Figure 6. If any situation matches the definiens, then the abstract term is appropriate. The process of matching will be discussed later.</Paragraph>
      <Paragraph position="10"> The definiendum can also be any concept, the choice is fdiosyncrattc; there is no reason why this device cannot be used with apparently non-abstract concepts, for example, a dog could be &amp;quot;man's best iriend&amp;quot; for sowk, in contrast with a non-abstrabt definition of &amp;quot;canine animal&amp;quot; Wn-abstract definitions have the form &amp;quot;genus-specificata&amp;quot;. In the encyclapedia, the representation is made up from a node related by variety to the genus (animal), to which are attached the properties in the specificata (canine) Rumelhart and Ortony (1976) use a relation similar to metalingual, ISWHEN, but do not show how participants are equated fn the definiendum and definiens, nor the processes that use such definitions.</Paragraph>
      <Paragraph position="11"> The metalingual arc is used in another context* Some propositions contain embedded propositions. For uniformity it ie desirable to restrict participation in propositions to entity nodes. Thus the matrix proposition has an unnamed participant in objective or instrumental role and this nsde is defined by a metalingual arc to the modality of the contained propositiono For example</Paragraph>
    </Section>
    <Section position="5" start_page="72" end_page="72" type="sub_section">
      <SectionTitle>
.Status Relations
</SectionTitle>
      <Paragraph position="0"> Knowledge in an encyclopedia is a model of the beliefs of one person. Nevertheless the knowledge is not all of the same status. In addition to containing the person s beliefs, it ~ncludes representcation of beliefs about his own desires and of his bcliefs about the beliefs and desires of others. His personal beliefs and desires interpret, control, and direct his personal activities. The knpwledge about others 1s the basis for interacting and communicating with them.</Paragraph>
      <Paragraph position="1"> For example, a conversation with a child about the structure of matter is quite different from one with a nuclear physiclet because of different conceptions about their levels of knowledge and hence what can be taken for granted. One has knowledge about individuals, e-g., your brother, Nelson Rockefeller, etc ., and about groups, e.g., politicians, sports wr lters, Russlans , etc.</Paragraph>
      <Paragraph position="2"> A disti-ncti on can be made between subconscious and conscious knowledge. Tbe former is, for example, the knowledge of language underlying its use or (2).</Paragraph>
      <Paragraph position="3"> (2) The Sun Circles the Farth.</Paragraph>
      <Paragraph position="4"> Conscious knowledge is learnt or communicated knowledge, e .g -, what one has been taught about the solar system. here is no reason for the two krnds of knowledge to be in accord regarding the same enti ties . One has learned, for example, that the Farth circles the Sun.</Paragraph>
      <Paragraph position="5"> Subconscious beliefs of self are unmarked in the encyclopedia.</Paragraph>
      <Paragraph position="6"> Subconscious beliefs of another are indicated by a believe arc between a node representing the believer and a modality node aovering the network representaion of the content of the beliefs. The subconscious belief of (2) by &amp;quot;people&amp;quot; is given in Figure 8.</Paragraph>
      <Paragraph position="7"> Figure 8 Knowledge status Conscious beliefs are represented as propositions embedded within an event &amp;quot;beLieve&amp;quot;. An example is given in (1) with its representation in Figure 7.</Paragraph>
      <Paragraph position="8"> It is not only propositions that have belief status, but also simple concepts, e .g ., ghosts. To accomodate this information, the placing of modality nodes is generalized. Previously only proposf tions were associated with modalities; now any node can have its own modality. On this modality information about a concept's existence and belief status can be represented, as in Figure 8 for &amp;quot;Fred Smith&amp;quot;. It is unlikely that each node or proposition is immediately linked to its believer. Using part-whole relations and modality nodes, domains ob belief, which may intersect, can be created as in Figure 8 for &amp;quot;Hugo&amp;quot; .</Paragraph>
      <Paragraph position="9"> Hendrix (1 975) partitions semantic networks to delimit domains of belief; here the same effect is gained through the use of modality structures.</Paragraph>
      <Paragraph position="10"> The desires of people are situations that they would llke to exist. The content of these goals can be represented by a modality covering (complexes of) propositions or single concepts, e-g., peace-If the goals are subconscious, a desire relation links the desirer to the modal ty. For consczous states, the modality is part of a metaliagually defined object ve of an event &amp;quot;desire&amp;quot;. In modeling behavior, these goals provide the situations that other b ehaviotal actions are intended to contribute towards achieving Negation Negation is a property that is marked on 4 modality. The most common site for negative marking is a propos:itional modality- Thus Fig~e 9 contains the proposition &amp;quot;I do not like tomatoes&amp;quot; \like 1  When some other constituent of a sentence is negated, say using strong stress, this is marked on a corresponding modality, so &amp;quot;John did not hit Mary&amp;quot; is encoded as in Figure 9.</Paragraph>
      <Paragraph position="11"> It is not anticipated, that negation is a common feature in knowledge, for &amp;quot;A person sometimes learns a negative fact when it cont'radicts something that might be inferred by mistake or that is true for a similar concept But, most negative facts are never learned'' (Collins &amp; Quillian, 1972, p . 319).</Paragraph>
      <Paragraph position="12"> Inheritance A node will inherit properties from nodes higher in its paxadigmatic path* Quillian (1969) used superset relations for the same purpose. In Figure 2, B inherits the properties of A, C those of B, D those of E, and E those of D. Inherihance is transitive, thus E inherits properties from A, B, C, and D. This permits parsimonious representation of properties: A property need only appear at the ancestor of concepts having the property. Inheritance is inhibited only if the inheritable property is contradicted on a lower node. For example, although the property &amp;quot;fly&amp;quot; may be associated with &amp;quot;bird&amp;quot;, it is prevented from being inherited by &amp;quot;penguin&amp;quot; by having explicitly &amp;quot;penguin not fly&amp;quot;.</Paragraph>
      <Paragraph position="13"> The generality of inheritance depends on the form of representation of the property at the ancestor node. Properties that are universally true at all times, e.g., birds have wings, are attached directly to a varietal node and are obligatorily true of all descendents. If at any time a bird without wings were reported, it would be cause for further explanation. Some other properties are always true but only at intermittent times, e.g., people eat, whose representation involves the manifestation relation. It is not odd that a person can be seen not eating, but if you watched long enough, it would be fully expected to obeerve this behavior sometime Finally there are occasional properties that make use of the typical arc in their representation. These proper ties are not universal, being merely noteworthy recollections about a concept, e.g., The French are rude. It would well be possible to have a complete history of an example of the concept and not witness the property without being disturbed by its absence.</Paragraph>
      <Paragraph position="14"> Episodic andL Sys ternic Memory Tulving ( I 972 ) distinguislles episod ic from semantic memory. The former &amp;quot;receives and stores information aboht temporally dated episodes or events, and temporal-spatial relations between events&amp;quot; (p. 385). TH~ 'latter is knowledge a person posse sses about words and other verbal symbols, tl~ear meaning and referents, about relations among them, and about rules, formulas, and algorithms for the manipulation of these symbols, concepts , and relations. Sqhan tic memory does not register perceptible properties of ~nputs, but rather cogni tlve referefits of inpbt signals. (p. 386) Abelson (1975 ) distinguishes episodic from propositional memory, and Woods (1975) contrasts intensions with extensions along similar lmes. The term I prefer, following Hays (1978), is systemic rather than semantic, propositional , or in tensional The localization in space and time of knowledge is represented .in the encyclopedia by spatial and temporal organization of propositions using the appropriate d&amp;scursive relations. A proper subpart of episodic memory is contained in paradigmatic organization. Nanifestations of instances (remember there are also manifestations of varietal and typical nodes, so it must be thus stated) represent spatio-Qemporally localized inf onnation about members of categories Consequently' knowledge represented on manifestations of instances, or their manifestations, is in episodic memory. This is only part of episodic memory as categorical knowledge can also be present. For example, in &amp;quot;Jung changed our view of dreams&amp;quot;, the reference is to the categorical notion of dreams, not to any specific ones. Nor is it sufficient for a proposition to have a non-categorical participant to be m episodic memory for &amp;quot;Prior to the Revolution. Russf an peasants were feudal serfs&amp;quot; cnotdins catpgorical gartici pants, yet is episo~ics The total extent of episodic memory is yltimately decided through spatial and temporal relatiion of discursive organizati~n, not by paradigmatic structure.</Paragraph>
      <Paragraph position="15"> Ouan tif ication para dig ma ti.^ arcs have the capability of capturing the essence of quantification, .including scope To illustrate the facility, cons:ider  Xf for a given c.orister in (4) it is necessary to determine the song he knows, i be., to evaluate the Skolem function, the information is present as a predication of that individual and should be retrieved using his name, say &amp;quot;George&amp;quot; and r rink to me only with thine eyes&amp;quot; -in Figure 10.</Paragraph>
      <Paragraph position="16"> It is also possible to give distinot representation to unquantlfied statements, such as (7), as in Figure 10.</Paragraph>
      <Paragraph position="17"> (7) A person likes candy.</Paragraph>
      <Paragraph position="18"> Paradigmatic arcs are here achieving reoresentational power equivalent to the partitioning of networks by Hendrix (1975)-30- null The above is a systemic rendition of &amp;quot;all&amp;quot;. The quantification can also be characterized episodically by every manifestat&lt;on of a concept having the property. Interpreting &amp;quot;all&amp;quot; (Woods, 1975), could call upon either systemic or episodic facts* A question containing a universal quantifier may be answered by either examining a varietal node (Are all moil-boxes blue?), or by = examining every mhifestation (Do a11 mail-bo~es stand at street corners?).</Paragraph>
      <Paragraph position="19"> It should be noted that &amp;quot;all&amp;quot; requires that the predicacron be true only at some time, e.g., All people die; it does not require continuity in time, e .g., All birds have wings. Thus untiversal quantification is also true if the predication is found for a manffestation of the varietal node, os is found for every instance of the concept. Processes in the Network  --The model for knowledge described above is only part of a system to model cognitive behavior. Thought is simulated by processing knowledge. Different aspects of behavior correspond to different processes, but with one and the same encyclopedia common to all. A system for discourse analysis requires processes that use the encyclopedia to find patterns of organization in a discourse. It would be possible to describe solely the requirements of discourse analysis, but greater overall insight is garned through a preliminary general examination and classification of cognitive processes. Once this is accomplished, discourse analy4s is seen not to be a unique process but as composed of more basic general ones. Simulation of many asp'ec ts of cognitive behavior can he porfomed by complexes of these general processes: discourse analysis is just an6 such complex Processes can be classified in various ways: functionally, by complexity, or by the class of relation involved.</Paragraph>
      <Paragraph position="20"> The ftlnction of some processes is external; they deal with input and output. Some internal processes find relations between new information and knowledge already in the encycloppdia, others investigate the va1idi.t~ of new knowledge, etc.</Paragraph>
      <Paragraph position="21"> Processes are of two type oE complexity, either path-tracini or pattern-*. The dichdtomy is justified by showing that there are tasks that can only be done by pattern-matching* This topic i.s considered in detail later.</Paragraph>
      <Paragraph position="22"> Of the infinite number of possible ordered sets of arcs, only some define significant paths in the network. An example of a relevant set of arcs is the arcs of a paradigmatic path; this defines possible inheritances. Other significant sets are causal chains, whi-ch are represented by a string of cause arcs between modalities. Th~s suggests that processes that use tile same kind of relati,ons or identical relations are significant.</Paragraph>
      <Paragraph position="23"> A functronal classification of processes does nqt give a deeper understanding of3 cognitive processes. However, classification by complexity and by kind of arc is revealing. Path-tracing and pattern-matching differ in power. For the tormer, subpaths can be defined by the kind of arc found in the subpath. Henceforth processes in the network wilt be described according as they are path-tracers or pattern-matchers.</Paragraph>
      <Paragraph position="24"> Path-tracing  Path-tracing processes try to establish paths between nodes along arcs of the network. Quillian (1969) established this methodology for semantic nets. A particularly common type of path is the paradigmatic path. In rigure 3 there is a paradigmatic path betweqn &amp;quot;Ford (as President)&amp;quot; and &amp;quot;thing&amp;quot;, but not between &amp;quot;rock&amp;quot; and &amp;quot;soul&amp;quot;. The definition of a paradigmatic path is valid for entities, events, and attributes.</Paragraph>
      <Paragraph position="25"> Any paradigmatic path in the network will conform to the structure sl~own in Flgure 11 where * indicates any number of occurrences including zero of the marked relation.</Paragraph>
      <Paragraph position="26"> Figure 11 Paradigmatic paths The structure follows directly from the iterativity of variety, manifestation, and typical arcs and their posbible relative orien ta~ tions. Strings of arc labels representing paths throwh the tree are obviously regular expressions, Lee, the strings are sentences of a type 3 language* Paradigmatic path-tracing can thus be characterized by a finite sVate automaton (Hopcroft &amp; Ullman, 1969).</Paragraph>
      <Paragraph position="27"> Any process that can he characterized by a finite state automaton is formally termed a path-tracing prwess in the system* One such process is testing the applicability of an attribute to an entity, e .go, whether &amp;quot;fresh fish&amp;quot; or &amp;quot;round smoke&amp;quot; is acceptable when the relationship is not explicitly in the encyclopedia . Assuming the named entry points to the encyclopedia are at vari-ety or instance nodes, an entity F1 (e.g., horse) can inherit properties from an entity  C2 (e.g., animal) if there is a path between F1 and T2 of the form (I-) iiihR*, where indicates a relation that is the converse of X and ) ind~cate an optional arc. Properties may be attached to E2 either directly ar with typical and/or manifestation arcs, ime., the path from Cp to the node F3 in the representation of the property has the form TYP* MAN*. Thus the path from El to Eg has the form (m) WR* TYP* MAN*. Analogously, an attribute Al can apply to an entlty if there is a similar path to an attribute that :is encoded as applying to the entity. Thus if there is a path (8) '&lt;El &gt; (ET) KW TYP* MAN* GE IIAN* TYP* VAK* (IST) [Al I then A, can feasibly apply to El. That is to say, the explicit encod null ing of &amp;quot;emotional animal&amp;quot; would make it reasonable to infer &amp;quot;sad horse&amp;quot;. The path (8) is composed of paradigmatic patjis linked by a single application arc. Each segment is a regular expression. As type 3 languages are closed under concatenation (Hopcroft &amp; Ullman, 1969, theorem 3.8), it EollowS that (8) is also a regular expression and that attribute gpplicability testin8 is a path-tracing process.</Paragraph>
      <Paragraph position="28"> * Propositions in a discourse should be consistent wit11 encyclopedic knowledge. Consistency is established by finding a proposition in the encyclopedia that is a generalization of the discourse proposition, e.g., given the discourse proposition  (9) Harv gobbled the caviar.</Paragraph>
      <Paragraph position="29"> and finding the generalization (10) People eat food.</Paragraph>
      <Paragraph position="30">  A novel statement, e .g., &amp;quot;fiarry munched the spider&amp;quot;, which is not consistent with (10) (assuming &amp;quot;spider&amp;quot; is not a variety of &amp;quot;food&amp;quot;), would evoke a demand for further explanation, or similar. Consistency judgment can be formulated as a complex of path-tracing processes. In</Paragraph>
      <Paragraph position="32"> the network form of (9), &amp;quot;Marv&amp;quot; is the agent and caviar&amp;quot; is the objective of &amp;quot;gobble1'. Flgute 12 encodes (10).</Paragraph>
      <Paragraph position="33"> Figure 12 Consistency j udgment The words in the discourse proposition provide entry points into the network of Figure 12 through the dictionary and converse name relations* From &amp;quot;gobble&amp;quot;, node 1, paths along paradigmatic arcs are traversed tio locate nodes from which &amp;quot;gobble&amp;quot; could inherit properties, It eeg., node 2. Kext from the entries for &amp;quot;tlarv&amp;quot; (A), and caviar&amp;quot;, (B), analogous paths are followed, reaching C and D, respectively (among other nodes). From C and TI arcs corresponding to the participatory relations of &amp;quot;Marv&amp;quot; and of &amp;quot;caviar&amp;quot; to &amp;quot;gobble&amp;quot;, i.e., agent and objective, respectively, are followed. If all paths intersect at a single node, e .go, node 2, then the proposition containing the intersection is the general proposition sought. Each path from an entry point to an intersection can be characterized by a regular expression. There are only four case relations, which sets a finite upper bound to the number of paths to be followed. Hence this process is also a path-tracine proceqs.</Paragraph>
      <Paragraph position="34"> Lbcatlng existing knbwledge, propositions that are already explicitly in the encyclopedia, is effectively identical to the consistency testing process above, but with downward paradigmatic paths being followed instead of upward ones. Thus given &amp;quot;Oswald assassinated Kennedy&amp;quot; and the network of Figure 13,  defined terms If a discourse conf lguration matches a metalingual definition, then the part of the discourse so matched may be replaced by the term. Figure 14 contains representations of (a) &amp;quot;Fred ate some  cake that made him sick&amp;quot; and (b) the definition of poisonf':  If the latter matches the former, then poison&amp;quot; describes the discourse situation. Earlies a path-tracing process was used to establish consistency between a general and a specific proposition. The same process can be used to pair propositions or the discourse and the definition. However, there is an aspect of complexes of propositions that prevents path-tracing from being a complete solution. If the complex contains coreferential items, as &amp;quot;poison&amp;quot; does, this coreferentiality must be examined; if it were not errors could result. For example, consider a discourse containing &amp;quot;John's eating the worms made Fred sick&amp;quot;. Each proposition matches phrt of the definition of &amp;quot;poison&amp;quot;, but it should not be taken as an act of poisoning. The coreferentiality condition plevents a match. As, in general, there can he any number of coreferential participants in a complex of propositions, it is not possible to define a regular expression ta characterize the coreferentiality test. This can be shown by considering a definition of an abstract term that contains n coreferential concepts. There is in general no bound on dss the definition can contain any number of propositions. If a complex of discourse propositions is to match the def initton then there must first be a unique correspond tng proposition in the definition for each discourse proposition. This can be done using the path-tracing process described above. But over and beyond this, the coreference condition must be satistted . For each manifestation of the coreferential concept in the definition there must be a corresponding manifestatim of one and always the same concept in the discourse . Also the syntagmatic role of corresponding manifestations in their respective propositions mwt be the same* The acceptance condition involves pair-wise counting. This is equivalent to accepting n n strings of the form a b , which are not sentences in a type 3 language (Hopcroft &amp; Ullman, 1969). This demonstrates that processes that compare complexes of propositions containing coref eren tial items are not, in general, path-trac~hg processes.</Paragraph>
      <Paragraph position="36"> A process charac terired by a device more powerful than a finite ?utomrrton is formally designhted a pattern-hatching process.</Paragraph>
      <Paragraph position="37"> Paraphrasing discourse usinp metalingunlly def ineri terms is another sattern-matching process* lfatalinaual definitions can be recursively embedded. For example, &amp;quot;buy1' may be defined in terms of &amp;quot;pive&amp;quot;, which in turd may be defined in tens of &amp;quot;have&amp;quot;. Recursion is not a property of regular languages, hence this process is not 3 path-tracing plocesse Matching discourse conPS igurations against definitions, called abstraction, is an extension of the process that substantiates discourse propositions by seeking generali zed proposi tions in the encyclopedia, discussed earlier* The components of a definition are generalized propositions and hence the substantiation process will find them if they correspond to part of the discourse. Schematically, two discourse propositions DP, and DP1, may match generalized propositions  This is the normal output when judging consistency. Propositions of a definition are under a conjoining modality, to which the metalingual arc points. If it is found that Some af the general propositions are part of definitions, Lea, CP2 and GP3 in MLD, then these definitions are examined to see if all the conditions for their use are satisfied, *i.e., coreference and contextual (e.g., cause arcs) conditions. For example, in llpoison&amp;quot;, Figure 14, the coreference of the agent of &amp;quot;eat&amp;quot; and the applicand of &amp;quot;ill&amp;quot;. If a definition is satisfied, tKen the part of the a iscourse matching the definiens can be paraphrased.</Paragraph>
      <Paragraph position="38"> The definitional nets so far presented are not adequate for paraphrasing, but must be augmented 40 include the roles of entities of the definiens with respect to the definiendum. This is done with manifestation arcs. A network definition of &amp;quot;buy&amp;quot; (in &amp;quot;A buys thing from B for money1') is given in Figure 16. The verbalization is &amp;quot;A gives money to B and B gives thing to A&amp;quot;.</Paragraph>
      <Paragraph position="39"> Figure 16 Role correspondence The manifestation arcs indicate the role correspondences between &amp;quot;buy&amp;quot; and the defining situation as well as coreferentialities within the latter.</Paragraph>
      <Paragraph position="40"> The case correspondences are essential information for the prot ess of abstraction and for its inverse, decomposition, which produces a less abstract description from a network containing a term that has a metalingual definition. For example, given the sentence &amp;quot;John bought a bicycle from Jane&amp;quot;, the definition of Figure 16 enables the paraphrase &amp;quot;Jane gave a bicycle to John and John gave money to Jane&amp;quot; to be generated. &amp;quot;Money&amp;quot; was unexpressed in the original, but is present in the definition, and appears in the paraphrase. The process fills empty slots by the appropriate concept from the definition, in this case  money&amp;quot;. The agent, experiencer, and objective slots are filled in the source statement and are transferred to the paraphrase.</Paragraph>
      <Paragraph position="41"> Another abstract term can point to the same definitional network, say &amp;quot;sell&amp;quot; in the case of Figure 16. The net then has all the informa&lt;ion for paraphrases between the two abstract terms as well as for decomposition and abstraction* There is no productive relationship between the roles of the same participant at different Levels of abstraction. Case relations represent only the causal/animate perception of participation in an event. More detailed descriptions of the roles of participants can only be If given in context. For example, money&amp;quot; is perceived as instrumental in &amp;quot;buytt, but at the next level of decomposition, it is in an objectiue role in &amp;quot;give&amp;quot;.</Paragraph>
      <Paragraph position="42"> The outputs of both abstractton and decomposition are structurally indistinguishable from any other proposition in the encyclopedia and therefore can again be subject to either of the processes.</Paragraph>
      <Paragraph position="43"> As pattern-matching is a recursive process this ability for output of the process to be accepted as input is essential.</Paragraph>
      <Paragraph position="44"> The distinction between path-tracing and pattern-matching processes may be psychologically significant Inhelder and Piaget (1 964) find that prepuberty children cannot use logical equations such as -(A AB) 3 -A V -Be The equations involve cgreference and hence their application requires a pattern-matching process . It could be speculated that this more powerful process only appear&amp; at maturation.</Paragraph>
    </Section>
  </Section>
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