FINDING TRANSLATION EQUIVALENTS: AN APPLICATION OF GRAMMATICAL METAPHOR John A. Bateman* USC/Information Sciences Institute 4676 Admiralty Way Marina del Rey, CA 90292 U.S.A. (e-mail: bateman@isi, edu) April 4, 1990 Abstract linguistic structures generated by monolingual gen- erators for distinct languages for a given abstract se- In this paper I describe how a significant class of cases mantic specification to be structurally similar: there- that would involve (possibly complex) structural trans- fore, translations that involve very diverse structures fer in nmchine translation can be handled avoiding trans- are readily obtainable if they are semantically moti- fer. This is achieved by applying a semantic organization vated. Monolingual generation components of the developed for monolingual text generation that is suffi- type described are also independently motivated by ciently abstract to remain invariant, within theoretically language processing tasks that do not involve MT specifiable limits, across different languages. The further and so are ill any case required. Providing for their application of a mechanism motivated from within mono- usage within the MT context also is therefore doubly lingual text generation, 'grammatical metaphor', then beneficial. allows candidate appropriate translations to be isolated. The particular mechanism developed within text The incorporation of these essentially monolingual mech- anisms within the machine translation process promises generation that I will apply to MT problems here to significantly improve translational capabilities; exam- is that of grammatical raelaphor (Ilalliday, 1985); grammatical metaphor was originally developed ples of this are presented for English and German. within the tradition of Systemic-Functional Linguis- tics and is now beginning to be applied within 1 Introduction the PENMAN text generation system (Mann and Matthiessen, 1985; The Penman Project, 1989). Historically there has rather little interaction be- Systemic-functional linguistics posits sets of map- tween work in text generation and machine trans- pings between semantic information to be expressed lation (MT) -- even though language generation and grammatical features. One class of mappings is needs to be an integral component of any cornplete termed 'congruent', in that it offers an unmarked re- MT system. Current text generation systems are, alization of a semantic concept type -- e.g., that however, achieving results which can be beneficially a processual semantic entity is realized as a ver- applied in the MT context. In this paper, I de- bal constituent in the grammar -- while a fur- scribe one such area of possible interaction between ther class of mappings is 'noneongrnent', in that it. mechanisms developed for monolingual text gener- enables marked correspondences between semantics ation and the requirements of MT. In particular, and grammar --e.g., in nominalizations where a the increasing concern that text generation theories processual ,;emantic entity is realized as a nominal show for higher levels of semantics and its realization constituent in the grammar. Below I show how the in linguistic form makes it possible to move away set of linguistic structures related by grammatical from lower-level, 'structural' transfer between lan- metaphor form a useful equivalence class for MT: i.e., guages. In Iket, some of the semantic specifications when seeking an appropriate translation tbr some now being uncovered within text generation arc suf- sentence, one will often be found in the set of tar- ficiently abstract as to capture significant informa- get language sentences formed by generating from tional invariances across languages. Sophisticated the corresponding abstract semantic specification in- monolingual generation components are able to gen- voldng grammatical metaphor for variations in the erate appropriate linguistic structures from such ab- structures generated. stract informational specifications. This avoids, in To show how this works in more detail, I first de- many cases, problems of (possibly complex) struc- scribe the level of abstract semantic information that tural transfer. There is no reason a priori for the is currently used within the PENMAN system -- this we term the upper model- and the user interface to *Much of the work reported here was carried out with the financial support of the Institut fi',. Angcwandte hfformations- the text generation system that it. supports -- which forschung at the University of the Saarland, S~mrbri'mken', ad- is called SPL. Second, 1 provide more concr¢~te exam- ditional support was provided by AFOS[{ contract, F49620-87- pies of two distinct kinds of grammatical metaphor C-0005, and in part by DAI{PA contract MDAg03-87-C-641. that we can now implement compntationally. And The opilfions in this report arc solely those of the author. Thanks are due to Erich Steiner, Jgrg Schi'ltz, and C (~cilc Pro'is finally, I go on to show their applica~:.ion to MT using for significant contributions. examples from English and German. i 13 / // 2 The Upper Model and SPL inalienable-possessions of that actor. 1 The position- ing of the general types and relationships within the The PENMAN tipper model organizes the 'proposi- upper model provides much of the information that tional type' meanings that need to be expressed in a grammar needs for constraining possible surface text; it provides a general semantic taxonomy of realizations. 2 classes of experiences and objects. This classifica- tion can also be seen as an inheritance hierarchy that organizes concepts according to how they may be ex- 3 Grammatical Metaphors pressed. For example, the inheritance of certain roles defines the types of participants that processes may A powerful property of the relationship between the have and the types of qualities that may be ascribed upper model and the grammar is the existence of to particular objects, while class-subclass relations grammatical metaphor. Grammatical metaphor oc- capture generalizations about possible grammatical curs when meanings are realized through 'nontypical' and lexical realizations of concepts. Significantly, selections of grammatical features; such realizations this orientation towards supporting grammatical re- can be described systematically and bring their own alization renders the upper model independent of distinctive contributions to the meaning expressed particular domains -- the semantic taxonomy offers (for a general typology, see Ravelli, 1985). Two types an organization that is required for any domain if it is of grammatical metaphor which we are beginning to to support natural language generation. Rather fine be able to control computationally are rankshifling distinctions are drawn by the current upper model, and complexity metaphors. Figure 1 shows the first which contains approximately 200 concepts; details grammatical decisions that must be made when be- are provided in Bateman, Kasper, Moore, and Whit- ginning generation of a grammatical unit according ney (1990). to a systemic-functional grammar such as that used within PENMAN. For each meaning to be expressed, The upper model supports specifications of sen- tence 'meaning' that may serve as input to a text grammatical decisions must first be made as to the generation system (Kasper, 1989a), or as output rank of the grammatical unit that will be used -- from an analysis component (Kasper, 1989b). Such i.e., clauses, groups (nominal, verbal, adverbial and specifications, which are expressed in the PENMAN prepositional), words, and morphemes -- and the Sentence: Plan Language (SPL), abstract beyond complexity of that grammatical unit -- i.e., whether many syntactic variations; they capture basic mean- the unit is a single unit or some combination of simi- ings -- defined in terms of the upper model -- that lar units (e.g., conjunction). Traditionally, the map- may be given a variety of linguistic realizations de- ping between meanings to be expressed and these pending on other, specifiable, criteria. One conse- grammatical choices has been rather inflexible and quence of the abstractness of this representation is limited to congruenl realizations; i.e., by and large, a that many sentences taken from distinct languages process-type meaning (activity, state, etc.) would be that would require complex structural transfer for realized by a selection of a simple clause, an object- translation simply share a common SPL representa- type meaning by a selection of nominal, etc. Gram- tion, thus requiring no transfer at all. However, it is tactical metaphor makes explicit the fact that this important to note that this is motivated by a com- relationship between meaning and grammatical form monality in linguistic function when a sufficiently ab- is considerably more flexible and many noncongruent stract standpoint is taken rather than on any claims realizations are possible. of universality; further details on the theoretical sta- Consider, for example, the SPL specification for tus of the shared representations are presented in example sentence (2) The discharge of electricity re- Bateman (1989). We will see examples of the avoid- suited in a breakdown of the system. ance of structural transfer in Section 5. ((cO / cause-effect :domain discharge A simple example of an SPL specification using :range breakdown) the upper model is shown below. This shows the (discharge / directed-action SPL specification for the sentence: (1) Mary cut her :actee (electricity / substance)) (breakdown