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<?xml version="1.0" standalone="yes"?> <Paper uid="W98-0720"> <Title>References</Title> <Section position="1" start_page="0" end_page="0" type="metho"> <SectionTitle> SRI International </SectionTitle> <Paragraph position="0"/> </Section> <Section position="2" start_page="0" end_page="0" type="metho"> <SectionTitle> Abstract </SectionTitle> <Paragraph position="0"> This paper presents a method for deriving metonymic coercions from the knowledge available in WordNet. Two different classes of metonymies are inferred by using (1) lexico-semantic connections between concepts or (2) morphological cues and logical formulae defining lexical concepts. In both cases the derivation of metonymic paths is based on approximations of sortal constraints retrieved from WordNet. null This novel method of inferring coercions validates the related knowledge through coreference links. As a result, metonymic coercions are potentially useful for the recognition of coreferring entities in information extraction systems.</Paragraph> </Section> <Section position="3" start_page="0" end_page="142" type="metho"> <SectionTitle> 1 Problem description </SectionTitle> <Paragraph position="0"> The pervasive phenomenon of metonymy raises a problem for the interpretation of real-world texts.</Paragraph> <Paragraph position="1"> Metonymies are figures of speech in which, according to the literature definition from (Lakoff and Johnson, 1990), &quot;one entity is used to refer to another, that is related to it&quot;. Characteristic of a metonymic reading of a textual expression is the fact that the satisfaction of sortal constraints guides the coercion to related knowledge.</Paragraph> <Paragraph position="2"> The comprehensive account of the semantics of meaning transfers presented in (Nunberg, 1995) indicates that coercions need to be embedded in a conceptual and lexico-semantic space, ideally provided by a linguistic knowledge base. Nunberg also notes that coercions are licensed by pragmatic circumstances, specifically pertaining to the Gricean principles (Grice, 1975).</Paragraph> <Paragraph position="3"> In this paper, we revisit the notion of metonymy and address the computational aspects of its resolution in the context of the relational semantics provided by the recently released WordNet 1.6 lexical database (www.cogsci.princeton.edu/~wn ).</Paragraph> <Paragraph position="4"> Following the lessons learned from the WordNet-based inference of Gricean implicatures, reported in (Harabagiu et al., 1996), a novel methodology of producing metonymic paths was devised.</Paragraph> <Paragraph position="5"> The coercions combine WordNet relations with st'- null mantic information derived from conceptual definitions. In WordNet (Miller, 1995) synony m words are structured in synsets, underlying a linguistic concept. Every synset is associated with a gloss, representing a textual definition, that can be translated in a logical form following the notation introduced in (Hobbs, 1986-1). This formalism, used in the implementation of TACITUS (Hobbs, 1986-2), accommodates a large variety of discourse inferences and, moreover, provides an elegant manner of localizing ambiguities, as was shown in (Bear and Hobbs, 1988).</Paragraph> <Paragraph position="6"> Conceptual support from linguistic knowledge bases was already considered in the implementation of several metonymy resolution systems (e.g. (Markerr and Hahn, 1997), (Fass, 1991) (Hobbs. 1986-2)), but none of these systems provided with more inferential flexibility than the typical coercion classes formulated by Lakoff (Lakoff and Johnson, 1990).</Paragraph> <Paragraph position="7"> We propose here a metonymy resolution approach that accounts for an open class of coercions. Similarly to Nunberg (Nunberg, 1995) and more recently to Markert and Hahn (Markert and Hahn, 1997), we find metonymy and nominal reference resolution to be two interacting processes; therefore, the proposed computational model validates metonymies through coreference links.</Paragraph> </Section> <Section position="4" start_page="142" end_page="144" type="metho"> <SectionTitle> 2 Classes of metonymic coercions </SectionTitle> <Paragraph position="0"> Stallard proposed in (Stallard, 1993) a distinction between two kinds of metonymy: (1) referential raetonymy, in which the referent of a nominal predicate argument requires coercion and (2) predicative metonymy, featuring the coercion of the predicate usually corresponding to a verbal lexicalization. In his study, Stallard focuses on metonymic inferences required by a specific performative context, characterized by wh-questions and imperatives. His formalization of referential and predicative metonymies is based on the logical form readings of utterances from the DARPA ATIS (Air Travel Information Service) domain (MADCOW. 1992), a question-answering database about commercial air flights, comprising questions of the form:</Paragraph> <Paragraph position="2"> (QI) Vhich wide-body jets serve dinner? (Q2) Which airlines fly from Boston to Denver? The ATIS domain is characterized by a pre-established formal system of categories and relations onto which the utterances must be mapped. In this domain it is known that only flights fly or serve meals; thus, both (Q1) and (Q2) can only be understood metonymically. The interpretation of the ATT$ utterances is performed in the logical language imposed by the implementation in the DELPHI system (Bobrow et al., 1991). In this framework, a question is translated into a LISP-expression: (wh x S (and (PI x) (P2 x)) interpreted as a query for all members of S (the semantic class of the wh-NP) that satisfy both PI (defined as the modifiers of the wh-NP) and P2 (the predicate of the clause). For exemplification, (qLFi) and (0LF2) represent the logical form translations of (QI) and (Q2)t:</Paragraph> <Paragraph position="4"> In the case of (QLFI), the coercion relation aircraft-of maps between flights and the aircrafts they are on, whereas in the case of (QLF2), the coercion relation airline-of translates the connection between airlines and flights. Although both (QLFI) and (qLF2) have an interpolated quantifier for flights, which is not specified in the utterance, the difference comes from the position of the variable: in the case of (QLF1), the interpolated variable x is the wh-variahle, whereas in the case of (QLF2), the interpolated variable y is part of the description that should be returned by the query. Stallard notes that this is the crux of the referential/predicative distinction of metonymies.</Paragraph> <Paragraph position="5"> In (0LFt), the NP-argument jets does not represent the domain of the wh-variable, but flight; does, thus indicating a metonymic reference and deriving a referential metonymy reading. In contrast, in (QLF2) the domain of the wh-variable coincides with the semantic type from the utterance (i.e., airlines), but the subject-argument of the fly predicate is replaced by the coercion flights.</Paragraph> <Paragraph position="6"> This prompts Stallard to state that &quot;predicative I (Or), (Q2), ({~LFt) and (qLF2) are borrowed from (StaJlard, 1993) metonymy can be loosely thought of as coercion of a predicate place, rather than that of the argument NP itself&quot;.</Paragraph> <Paragraph position="7"> We argue that this definition is dependent on two factors: (1) the specific logical transformation imposed by the DELPHI implementation, which does not cover forms of utterances other than whquestions, and (2) the availability of thematic role relations and coercions tailored specifically for the ATIS domain. This characterization of referential/predicative metonymies is not applicable when processing different genres of text, operating in different domains and, thus needing a different knowledge representation. An example ofa metonymy resolution system using a more general representation is reported (Markert and Hahn, 1997).</Paragraph> <Paragraph position="8"> In their model of metonymy inference, Markert and Hahn employ a two-tiered conceptual and semantic test: conceptual checks identify well-formed role chains between a pair of syntactically linked concepts, and then semantic checks distinguish whether these chains mirror literal or metonymic relationships. To perform these checks, they use (1) a concept hierarchy C with a taxonomic relation isac and (2) a set of relation names 7~, containing labels of all conceptual roles of the elements from C, hierarchically organized by isa~. For the ATIS domain, we can assume C = {AIRLINE, JET, MEAL, PASSENGER, PILOT .... } and 7~ -- {has-aircraft, has-flight, property-of' serves, fly-from, fly-to .... }. To be able to parse texts, Markert and Hahn devised a system that grants a syntactic link between two concepts z and y if there is an acyclic path of relations ri E 7~ and concepts cj E C such that each ri is a conceptual role of ci-t, with ra,lge(ri)= ci and co = z A (c, isac. y V y isao ca).</Paragraph> <Paragraph position="9"> Following established classifications (Lakoff and Johnson, 1990), Markert and Hahn predefine some of the relations from ~ as metonymic. These relations are {has-part, part-of, produced-by, containedin, made-of}. Thus, a metonymy is recognized whenever one of the relations ri from a path is metonymic.</Paragraph> <Paragraph position="10"> In this framework, the interpretation of the relation between x =airline and y =dinner in (Q1) is rendered by the Path-l: c0--company (with z&quot;=airline-isa-~company), rt-'has-part, ct= employee (with flight-attendant-isa-+ employee and range (serve, SUBJECT) = flight-attendant), r2=serve, c3=meal (with y--dinner-isa-+meal).</Paragraph> <Paragraph position="11"> Similarly, the interpretation of the conceptual relatedness between r--airline and y=Boston in (Q2) is rendered by the Path-2: co=airline, rt=hasflight, cl=scheduled-flight, r2=arrive-at, c3=city (with y--Boston-isa-~city).</Paragraph> <Paragraph position="12"> The presence of rl=has-part in Path-I and of rt=has-flight in Path-2 indicates that the two</Paragraph> <Paragraph position="14"> paths correspond to metonymic readings. Relation has-flight is not among the predefined metonymic relations considered by Markert and Hahn, but clearly would need to be so, to classify Path-2 as metonymic. Moreover, as a distinction on the predicate coercions, Path-1 contains the relation rz---serve, identical to the wh-predicate of (Ol), indicating that it is not a predicative metonymy.</Paragraph> <Paragraph position="15"> The referential metonymy from Path-1 is determined by the metonymic relation rl=has-part, coercing airline to flight attendants. In contrast, Path-2 has relation r2-arrive-at that coerces the wh-predicate fly-to from ({~2).</Paragraph> <Paragraph position="16"> Markert and Hahn do not analyze the semantics of the metonymic paths, but instead distinguish referential and predicative metonyrnies only in the anaphoric cases. Considering that expression A is a metonymic coercion of the concept B, they assume that in the predicative case A should be available for reference resolution, whereas in the referential case, only B should be so. To be able to assess the availability for reference resolution, they search for the presence of A and B in the list of forward-looking centers of the previous sentences (thus using the functional centering framework defined in (Grosz et al., 1995)).</Paragraph> <Paragraph position="17"> A similar path-finding methodology for deriving metonymies was used by the met* system (Fass, 1991), in which connections between the sense frames of textual concepts are retrieved from a lexicon of the size of 500 word senses. These paths are then classified against a small set of predefined metonymic inference rules, and form the grounds for the figurative interpretation of textual expressions.</Paragraph> <Paragraph position="18"> In met* there is no support for distinctions between predicative and referential metonymies, since coercions are possible from any concept in a text. The appeal of this implementation stems from the fact that it uses word sense frames, inspired by the structure of dictionary entries and shows that the paths retrieved from such a knowledge representation can be used to identify classical forms of metonymy.</Paragraph> <Paragraph position="19"> This indicates that metonymy resolution can be performed by processing knowledge from lexical dictionaries, and therefore WordNet 1.6 is a suitable candidate. null A different methodology of deriving coercions was implemented in TACITUS (Hobbs et al., 1993).</Paragraph> <Paragraph position="20"> Whenever sortal constraints are violated, explicit arguments are replaced with coercion variables, related to the explicit arguments by generic relations. The coercion is devised when the generic relation subsumes some predicate that is brought forward by the abductive interpretation of the text. In the case of (Q1), argument jets is replaced with a coercion variable L- which is expected to satisfy the subjectconstraints of the verb serve. The abductive inter- null pretation of (Q1) brings forward a reasoning path showing that variable k may be coerced to any subsumer of concept person. Such a subsumer is synset {steward, flight attendant}, having the gloss (an attendant on an airplane). This gloss translates the generic relation between jets (a hyponym of airplanes) and variable k to the predicate on, cued by the prepositional relation attendant-on-+airplane.</Paragraph> <Paragraph position="21"> The interpretation of this prepositional relation is produced when it is matched against WordNet-based classes of prepositional attachments collected from large treebanks, following the methodology described in (Harabagiu, 1996). For this case, the onprepositional relation attaches the place of work to the worker, thus giving meaning to the coercion of jets into flight attendants.</Paragraph> <Paragraph position="22"> Although the coercions derived in TACITUS do not distinguish the predicative or referential cases, they present a different method of building metonymic paths. By incorporating this unification-based mechanism of producing coercions with a lexical path-finder working on WordNet, a novel way of deriving metonymies is made possible. It has the advantage that it relies only on approximations of sortal knowledge, as indirectly available from the WordNet database, and it does not need full-fledged abductions to be able to return metonymic paths.</Paragraph> </Section> <Section position="5" start_page="144" end_page="145" type="metho"> <SectionTitle> 3 Metonymic paths </SectionTitle> <Paragraph position="0"> The process of deriving metonymic paths from WordNet consists of three distinct phases: (1) the identification of sortal constraints that need to be satisfied during the interpretation of nominal expressions, (2) the retrieval of related knowledge that complies with the sortal restrictions, and (3) the validation of coercions against anaphoric expressions from the sentences following the processed sentence.</Paragraph> <Paragraph position="1"> The first two phases rely on access to semantic information available in (1) the relational semantic encoded in WordNet (e.g., hvpernyms, is_part, is_member, is_stuff&quot; entail or pertaymym) spanning synsets or words encoded in the database and (2) the semantic of the synset definitions (known as glosses). To be able to have computational access to the gloss semantic, synset definitions have been translated into logical formulae inspired by notation proposed in (Hobbs, 1986-1) and implemented in TAClTUS.</Paragraph> <Paragraph position="2"> Based on the davidsonian treatment of action sentences, in which events are treated as individuals, every gloss is transformed in a first-order predicate formula for which (1) verbs are mapped in predicates t,erb(e,z.y) with the convention that variable e represents the eventuality of that action or event to take place, z represents the subject of the action. and Y represents its object (in the case of intransitive verbs, Y is not attached to a predicate.</Paragraph> <Paragraph position="3"> whereas irt the case of bitransitive verbs, y is assumed to range over both the direct and indirect object); (b) nouns are mapped into their lexicalized predicates and (c) modifiers have the same argument as the predicate they modify. Prepositional attachments are indicated by preposition-predicates ranging over the pair of arguments of the predicates they attach. For example, the gloss of synset {airline, airline business, airway} is (a commercial enterprise that provides scheduled flights for passengers) and has the following logical form transformation (LFT): \[ea~ ezptise (x) ~:co~ereial (z) &provide (e, x, y) & ~:t li~cht (y) ~scheduled (y) ~f or ( e, p) ~passenge:r (p) \] Characteristic of LFTs is the fact that the gloss genus is always the first predicate, rendering the LFT a formula of the form \[genus(x)g:differentia(y)\].</Paragraph> <Paragraph position="4"> Gloss geni are accessed repeatedly during the derivation of metonymic paths, and thus they need to be easily accessible.</Paragraph> <Paragraph position="5"> The first two phases of the metonymic inference relies also upon lexico-semantic relations determined by derivational morphology, specifically the links between verbs and their nominalizations. Relations between verb and noun synsets that have elements with common morphological roots have been added to the database, classifying them as (a) the action nominalization; (b) the result (or object) of the action or (c) the agent (or subject) of the action, For example, verb propose and noun proposal refer to the same action. A nominalization(act) link was established between verb synset {propose, pro jet1:} and the sense of proposal glossed as (the act o/making a proposal). A second nominali=ation(result) link was established between the same verb synset and the sense of proposal glossed as (something proposed).</Paragraph> <Paragraph position="6"> Phase h Approz~mation o/ the sortal constraints.</Paragraph> <Paragraph position="7"> A nominal N is interpreted as literal or figurative depending on whether its sortal constraints to syntactically linked verb V are satisfied or not. Sortal information can be found in: * (i) the LFT(g), where g stands for the gloss of any sense i of V (hence Vi) or any of its hypernyms; * (ii) LFT(e). where * represents an example from 8; * (iii) I, FT(c). where e represent those glosses where and V co-occur (and the sense of Y is unknown}.</Paragraph> <Paragraph position="8"> To access the sortal constraints of V implicitly encoded in WordNet, we collect all expressions from LFT(g) or LFT(e) such that: (1) they contain a predicate verbi(e~, x\[, x~), representing either (a) V/ or (b) one of its hypernyms or (c) one of the geni from the LFTs of I,~ or its hypernyms; (2} they also contain any predicate that is (a) a subject, (b) an object and/or {c) a prepositional attachment tO verbi in the same /..FT.</Paragraph> <Paragraph position="9"> When all predicates are conceptualized in the respective LFTs. such expressions have the form: Si ~ i i i verbi(el ,xz, x~) ~ subjecti{x~) ~ objecti(x~) &: l'Iflprepj(e~,yj) ~ nou.j(y~)) The sortal information for subjects and objects of</Paragraph> <Paragraph position="11"> (a) the subject from some Si (= S~) and (b) is the hypernym of any other subject (from another S~ ok) that belongs to the same WordNet hierarchy.</Paragraph> <Paragraph position="12"> Objecti(V) = Uk, objeet~,(x~ ~, ), where objectik, is: ' kt (a) the object from some Si (= Si ) and (b) is the hypernym of any other object (from another S~ 'ok') that belongs to the same WordNet hierarchy.</Paragraph> <Paragraph position="13"> Similarly, for each prepositional attachment determined by a preposition prep, we define the sortal information: Nouni(V ,prep) \[.Jk,, i i i = nounk,,(x t.~,,) where nounk,, is: (a) attached to verbi in some Si (S~&quot;) through prep and (b) is the hypernym of any other noun attached through prep (in another S~ ''gh''), when both nouns belong to the same WordNet hierarchy.</Paragraph> <Paragraph position="14"> Expressions S&quot; are collected from the r.xT(C/). The semantic sense k of V in S~ is selected as a result of the fact that the similarity measure between S&quot; and the collection {5; } is maximal when i = k. The similarity measure between two expressions is defined as:</Paragraph> <Paragraph position="16"> where for role E {subject, object,{prepj} } we have: (i) Sire(role. S~,, S~) = 1 if the conceptualizations of role(S~,) and role(Si) belong to the same hierarchy ... q.r (ii) Sire(role. S~,. Si) 0 when either role(~ ~) role(Si) are not defined or iii) Sire(role. S'~, Si) = -I otherwise.</Paragraph> <Paragraph position="17"> Finally, considering the set operator: St (~a $2 ={e \] e E St IJ $2 and there is no other e' E St LI $2 such that e' is a hyeprnym of e} the sorrel constraint approximations are defined as: rl Subject_SortdV)=Subjeeti(V) ~a \[Jq subject~, where subject~ is the subject from some S'~ in which the sense of V is i; r30bject.Sorti(V)=Objecti(V) ~h Uq, degbjectiC/, where objectS, is the object from some S~, in which the ~ense of V is i:</Paragraph> </Section> <Section position="6" start_page="145" end_page="146" type="metho"> <SectionTitle> \[3 Prep.Sort,(V,prep)=Nouni(V,prepl ~h UC/, ndeguni4 ', </SectionTitle> <Paragraph position="0"> where nouniC/, attaches to the sense i of V through prep in some S~.</Paragraph> <Paragraph position="1"> Phase IL&quot; Sorts satis\[action and expansion o\[ coercions. Sorts satisfaction amounts to (1) the recognition of the sense of V in the text and (2) a search for any element from Role-Sorti(V) across all concepts semantically related ro all WordNet senses of N (given that t/has the same role in the text).</Paragraph> <Paragraph position="2"> The recognition of sense i of V is based also on the maximal value of similarity between S,, the expression retrieved from the r~T of the text, and {Sort,(V)}. where Sort,(V) is defined as:</Paragraph> <Paragraph position="4"> The satisfaction of Role_Sorti(V) is a search for any element from this set along (1) all synonyms, (2) all hypernyms and (3) all ~ geni for each Word-Net sense of N. If this search is successful, we rule that N had a literal reading. Otherwise, we need to build metonymic paths to be able to access the related knowledge. Two distinct ways of deriving metonymic paths have been developed.</Paragraph> <Paragraph position="5"> Lezico-semantic paths. The codification of meronymic relations in WordNet determines the consideration of lexico-semantic paths composed of isa and at least one is_part, is_member, or is_stuff relations (or their reverses} as a means of deriving coercions. Implementing 22.20% of the semantic connections between noun concepts as meronyms, WordNet 1.6 sets an acceptable level of granularity for a knowledge representation needed to derive metonymic information.</Paragraph> <Paragraph position="6"> Lexico-semantic metonymies retrieve concepts Cm E Role.Sorti(V) that (1) are linked through a meronymic relation to any WordNet sense of N (or one of its hypernyms or geni); (2) morphologically or idiomatically indicate meronymic relations to N, or (3) represent predicates from the LFr of N (or its hypernyms) having thematic roles for the same verb that is the genus of the LFr. The general form of the lexico-semantic paths is determined to be PathLs = (Co--N, rhChr2 .... ,Crn), with at least for one i, ri is a WordNet meronymic relation. The case when a triplet (Cj_t,ri,Ci) is part of an LFT extends the classical metonymies object-for-agent and productfor-producer. null The WordNet concepts that morphologically cue meronymic relations are those synsets containing collocations of such lexemes as unit (e.g., administrative unit, army unit), system (e.g., exhaust system, file system), par~ (e.g. body part, academic department), group (e.g., jazz group, pressure group), or other words that form the same hierarchies as part to member. Similarly, concepts containing in their glosses idioms like ' 'a group of' ' or ' 'part of' ' cue meronymic relations to thegloss genus.</Paragraph> <Paragraph position="7"> Morpho-logical paths. Frequently, N is a nominalization ofa VN, and thus LFI'(VN) brings forward related semantic information. Moreover. the nominalization relations indicate the role of N in the r.Fr(E~): a nominalization(result) link corresponds to an object role. whereas a nominalization(agent) link relates to a subject role of N in the LFT(rv~).</Paragraph> <Paragraph position="8"> This entails the interchangeability of the genus of r.yr(N) with verb(e, zt,z~)&noun(zi) (with i=l if role=subject and i=2 if role=object) when verb is the predicate representing l,'h and noun is the predicate for N or any of its geni (in the hierarchies of the sense of N morphologically related to l/~v). The resulting logical form transformations are denoted as L~' (~).</Paragraph> <Paragraph position="9"> In this case, we can compute the Similarity(Text,LFT' (N)) and pick the Role(s) for which it is maximal and incorporate the corresponding LFTs in the most similar r.FT, (N), producing the final coercion. Morpho-logical paths are sequences of three kinds of steps: (1) relatedness based on morphological relations (i.e., N-nominalization-~VN), (2) adhoe weighted abduction based on similarity between text roles and the logical forms of the hypernyms of N (i.e. LFT' (N)-Similarity(text)~LFT(Roles)), and (3) unification of similar logical expression (i.e., LFT' (VN)-unification(LFT(text)-+Nc.</Paragraph> <Paragraph position="10"> Morpho-logic paths exploit morphological links and overlaps in the L~S and resolve predicative metonymies (by bringing into play additional verbal predicates). In contrast, lexico-semantic paths resolve referential metonyies.</Paragraph> <Paragraph position="11"> Phase III: Anaphora validation. Metonymic paths produce the expected coerced knowledge if they bring forward concepts that corefer with nominals from the successive sentences. There are three tests for the validation of coercions through anaphora. They determine whether there is a concept in a lexico-semantic path or a predicate in a morpho-logical path that (1) is identical, (2) is a hypernym, or (3) is a genus of one of the nonfinal expressions from the following sentences.</Paragraph> </Section> <Section position="7" start_page="146" end_page="147" type="metho"> <SectionTitle> 4 A case study </SectionTitle> <Paragraph position="0"> The processing associated with the derivation of metonymic paths is exemplified on a text presented in the manual defining the coreference task for the DARPA-sponsored MUC 7 competition (Hirshman and Chinchor, 1997): (S1) The White House sent its health care proposal to the Congress yesterday.</Paragraph> <Paragraph position="1"> ($2) Senator Dole said the administration's bill had little chance of passing.</Paragraph> <Paragraph position="2"> The approximation of the sortal constraints of 'C/=send from (St) determines: o (a) the selection of sense i=2 from the eight senses encoded for verb send in WordNet 1.6, due to greater similarity between its sorts and the roles from ($1).</Paragraph> <Paragraph position="4"> The search space for the sortal constraints is determined by the LFT of ($1):</Paragraph> <Paragraph position="6"> across the synonyms, hypernyms and geni of both WordNet senses of White House, the three senses of noun proposal and proper noun Congress respectively. null The WordNet search' for the satisfaction of sortal constraint identifies communication as the hypernym of sense 1 and 2 of proposal and person as the genus of {legislature,law_makers}, the hypernym of Congress, thus indicating that in (Sl), proposal and Congress have literal meaning. Noun proposal as a nominalization is a candidate for morph-logic path derivations as well. The search for sortal constraints for the role of subject is not successful, requiring the inference of metonymic paths. A lexico-semantic path is derived, linking sense 1 of White House to person, the genus of synset administrat ion: Pathl: llhite.Houso-isa--~govenmentAepartaent-- isa-+administrat ire_trait - morphological.zue-~ -+admiaistration--genus-~person The meronymic morphological cue from Pathl is consistent with the meronyms encoded in Word-Net 1.6, because we have: (a) govemment-department- is_part-+admirdstration as an immediate inference from Path1 (b) adminJstration-is_part--~government as a semantic relation encoded in WordNet 1.6 (c) govemment-department-is_part-.+government as a semantic relation encoded in WordNet 1.6 Moreover, the anaphoric validation of Pathl is possible because nominal administration is present in (S2).</Paragraph> <Paragraph position="7"> In the case ofObject2(send) a morpho-logical path accounts for the coerced knowledge. Nominalization proposal is the result of the action expressed by synset V'={ propose,project}. \[ntegrating predicate proposal as an object in the LFT(V') we obtain: LFT' (proposal)=present (e2, Yt, Y~)&proposal(y~ )& &for(e~, Ys )&consideration(ys ) When computing the similarity with (S1), we obtain Prep-Sort2(send,to) as the role candidate to be incorporated in LFT'(proposal). This is enforced by the LFT of synset {motion,question}, a hyponym of sense I of proposal. The gloss of {motion,question} is (a proposal for action made to a deliberative assembly for discussion and vote), producing the LFT: LFT( motion)=proposal{p)&for(p,d)&discussion(x)& &vote(x)&to(p,a)&assembly(a) in which present(e2,yt, y~)&proposal(y~) may substitute proposal(p)whereas discussion can be replaced by its hypernym considered:ion. Furthermore, since Congress is a hyponym of assembly and the filler of Prep_Sort2(send.to) in (S1). we can unify Lgr(motion), LFT'(proposal) and LgT(legislature) and obtain the final coercion as: proposal(p)=~present (e2, zl, z~. )&proposal(x2 )& &for(e2, x~)&consideration(3s )&to{e2, x2)& &person(x~ )&make(e~, x~,/)&law(l) Path2 is shown in its entirety in Figure 1. The anaphoric validation is shown to link bill from ($2) to la~, since law is a genus of the first WordNet sense of bill. Pathg brings forward two new actions (indicated by e2 and ea), which accounts for its classification as a predicative metonymy.</Paragraph> <Paragraph position="8"> The usage of the LFT of a hyponym of proposal is a consequence of modeling Gricean principles via lexical chains from WordNet. The relevance maxim is enforced whenever as many lexical chains as possible can be retrieved between previously activated concepts and novel information. When we process the sort satisfaction of the object role, concept legislature is already activated and it satisfies the Prep-sort2(sead.to) const raints. The same thematic role is represented in the LFT of mo~:ion, thus enlarging the number of \[exica\[ paths between proposal and legislature and increasing the relevance of logis:l.atttre in the context of coercing knowledge for the object proposal. The final unification reinforces the relevance of logisla~ttre, congruent with the coreferential link between bill and 1am</Paragraph> </Section> class="xml-element"></Paper>