Treating ‘Free Word Order’ in Machine Translation

Treating 'Free Word Order' in M mhine Translation 17,a,lf STEINBEI-/.GEII, UMIST - Centre for Comput;ational Linguistics Ma.uchesl;er, UK, r~flf(/;~ccl.umist.a,c.uk 0 Abstract In free word order languages, every s('.ni;cn(:(~ is cml)eddcd in its specific contexL The order of consl;ituenLs is d('tcrmincd l)y the categories theme, theme and contrastive J'oc'us. This pa- per shows [low to recognisc mid to transhti,e these cat;egorles autom;~t;ically on ;~ serH,e.n- tial basis, so that SCilI;ClIC(.' ('ml)edding; can I)c' achieved wit;houL having i;o tel'e,' 1,o l,h(', co,> t;cxt. Tradition,dly neglected moditier ch~sses are fully covered by the proposc'd mc'Lhod. 1 Introduction Most languages known as free word order hm- gv, ages are in facl; languages wil;ll parl, ially J)'ee wonl order (]';ngcN(amp el, al. 1992), or rather free phrase order (Schi;ufelc 1991). A difli- culty linl(cd to the form;d de.scription of i,}w.sc languages is that instead o17 a (:ompletc lack of ordering rules many sul)l, le rcsi;ricl, ions alj- ply. A large arrlounl, of wor(t or(lcr v;triai;ions ;trc gratnmi~t;ical in isoh~t<.d sct,tc,,:es, but co,,- text restricts the numl)er o1" s(K|uen(:es wllicli are possible and ilal;l~ll:al. Ill l,}lis s(.'llSC 1 Sell- fences air(', era, bedded in their context. A slw.- cific context calls for a certain word order, an(l the word order of a given senl, ence rcflect, s il,s conl;exl;. : ]n 1;his p;,pe,', we present ,'ccerit sugges- Lions on how 1;o treat, free lJhras(, order in N;d,- ural L~nguagc Processing (N],P), and [)?(?sent an alternative' solution t,o the problem. The id&~ is to use a the7natieall~-t.#ged, or fle:,:i- hie, canonical form (CI")for generation, and an algorithm to recognise the. re, levant cat- cgorics Ihe,te, "theme ;rod cont?'asZhm ./be'us du,'iilg ;m;dy.sis. 'l'his ,ncthod has })cc'n im- plcmctited successfully itl the u,tiflc;d, ion and constrainl.-basc'd M~vchine Tr;mslal,i(m sysl;em CAT2 (Sharp 71989, Sl;cinlmrgcr 1992a). I1, it> (:ludcs i;he ordering of ,nodi tiers, which arc l, ra- dil;ionally lcfI. oul; {,, wo,'d or(It,' desc,'il)l, iot, (C.o,,lo,,/l,;vet,s 71!1!)2). All stat;e, nc,~ts in (,his pN)cr concern writi,(m hmguage, ;~s spoken h.l- gu;tgjc is more ]i])er;d wil, h rcsl)eCl; to ordering. 2 The Data Wc shall stm'l. I)y prescni,ing some da.l,~ which illustral,cs the prol:~lc.ms re.hd,c.d to word ordc.r l, rc';d;inen(; in N],P. Many ordering wn'iations arc possible (1 ;~ - ] e, 2a, 21)), Iml, seine of them arc, less nal, tn';d (]c), and oI, h(.'rs arc ('.v('.n un- gramma.tical (2% 2d). 71('. is only accepl;ad)lc if I,}le pc','sotml protioun ich is heavily sl;rcsscd, indicatc'd here in capiLa.ls.' [at Mori;en2, i we?de ich Jim vielleichl.lv, besuchen. Tomorrow will I him l,'obabl:ll visit lh h:h wei'de, ihn vielh!ic.hl.lu ,,K)rg(mu,i bes,,(:hen. 1 will Dim probnbly Iomorrow uisil lc h:h we?de ihn i,,o,'geiluu vielhfichl;le beslichen. I 'will Mm lomorrow probably visil [d VielMchI.,., we,'de ich ihn ,noi'ge,~e,~ l)es,,che,,. Probably will 1 him lomo,'row visil le ? Moi'gen:t2 we.,'de ihn vMleichtl.., ICI1 besuchen. 7'omor~vw 'will him. prob~tbly visil 2a I",r fuhr dennoch~o ebenFalls:m nach Mi'mdmn. lie dro-ve never'th~less alsp to Munich 1The use of the index nmnbers will be explaim'.d in see.rich 5. 69 2b l)ennochun …

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