Processing Metonymy- a Domain-Model Heuristic Graph Traversal Approach

Processing Metonymy: a Domain-Model Heuristic Graph Traversal Approach* Jacques Bouaud, Bruno Bachimont, Pierre Zweigenbaum DIAM: SIM/AP-IIP A 1)el)t (te Biomathdmatiques, Universitd Paris 6 91, boulevard (le l'It6pital F-75634 Paris Cede.x 13 {j b, bb, pz }(<l)biomath.jussiou.fr Abstract We address here the treatment of me, tonymie expressions from a knowl- edge representation perspe(:tive, that is, in the context of a text understanding system whi('h aims to build a (:oncep- tual representation from texts according to a domain mode, l ext)resse, d in a knowl- edge representation formalism. We fo- cus in this t)aper on the part of tile se- mantic analyser which deals with seman- tic eoml)osition. We explain how we use tile domain model to handle metonymy dynamically, and more generally, to un- (lerlie semantic (:omposition, using tile knowledge descriptions atta(:hed to ea(:h (:oneept of our olttology as a kind of eon('el)t-h;ve.l , multii)b.-role (lualia struc- ture. YVe rely for this on ~t heuristic 1)ath search algorithm that exl)loits the gr~phic aspects of the eon(:eptual gratIhs formalism. The methods described have 1)een imi)lemente<l and applie(l on French texts in the medical domain. 1 Introduction []ii(ter the eomt)ositional assulnption, senmntie analysis relies on the combination of the mean- ing representations of parts to build the meaning representations of a whole. However, this con> position often needs to call on implicit knowledge whi(:h helps to link the two meaning representa- tions. This is the (:as(*,, for institute, in metonymi(" expressions, where a word is used to express a notion closely related to its central meaning. A well-known stream of work addressing this t)he- nomellon is the Generative Lexicon theory (Puste- jovsky, 1991). At the heart of this theory is a lex- ical semantic representation called "qualia struc~ lure", Met(mymies are considered to correspond to changes in the semantic types of the words in- *This work has been imrtly supporte, d by the Eu- tel)earn project MENELAS (AIM 2023). volved, and the qualia structure provides the basis for performing type coercion in a generative, way. We address here, the treatment of metonymie expressions from a knowledge representation per- spe(:tive, in the context of the MENF, I,AS medi- cal text understanding syste, m (Zweigenbaum et al., 1995). One of the goals of the overall system is to assign stan(tar(lised, medi(:al nomenclature codes to the input texts (patient discharge sum- maries). Semantic analysis st~rts from a syntac- tic representation of each sentence and produces a conceptual representation. It is then used by sev- e, ral language-independent, knowledge-based com- ponents to perform inferences (pragmatic enrich- nlellt) and then code assignment (Delamarre et al., 1!)95). Therefore,, the, conceptual represen- tation outtmt by the semantic analyser nmst be normalised: it must ('onform to a knowledge repre- sentation canon in which the target nomenclature (:odes can lie nlal)ped. 'l'he si)eciiication of this canon relies on the description of a rich model of the domain in a knowledge representation formal- ism, here Conceptual Graphs (CG) (Sowa, 1984). We focus in this patter on the part of the se- mantic analyser …

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