Granularity Effects in Tense Translation 
Michael Schiehlen* 
Institute ibr Comi)utational Linguistics, University of Stuttgart, 
Azenbergstr. 12, 70174 Stuttgart 
mike~adler, ims. uni-stuttgart, de 
1 Introduction 
One of the daunting problems in machine trans- 
lation (MT) is the mapping of tense. The paper 
singles out tile problem of translating German 
present tense into English. This problem seems 
particularly instructive as its solution requires 
calculation of aspect; as well as determination 
of tile temporal location of events with respect 
to the time of speech. We present a disam- 
biguation algorithm which makes use of gram 
ularity calculations to establish the scopal order 
of temporal adverbial phrases. The described 
algorithm has been implemented and is running 
in the Verbmobil system. 
The paper is organized as follows. In sections 2 
through 4 we 1)resent the problem and discuss 
the linguistic factors involved, always keeping 
an eye on their exploitation for disambiguation. 
Sections 5 and 6 are devoted to an abstract; def 
inition of temporal granularity and a discussion 
of granularity effects on scope resolution. In sec- 
tion 7 the actual disambiguation algorithm is 
presented, while section 8 describes its perfor- 
mance on the Verbmobil test data. A summary 
closes the paper. 
2 Present or Future? 
In contrast to English, the German present tense 
is commonly used to describe both present and 
future happenings. One task in translation from 
German to English is therefore tile dismnbigua- 
tion of German/)resent tense to present time or 
future time. 
(1) present tense ~ future time 
-+ present time 
* This work was fimded by the German Federal Min- 
istry of Education, Science, Research and Technology 
(BMBF) in the framework of the Verbmobil Project un- 
der Grant 01 IV 101 U. Many thanks are due to Profi 
H. Kamp attd K. Eberle. All errors are my own. 
2.1 Temporal Orientation 
A prominent factor involved in the choice be- 
tween present and future time (Butt, 1995) is 
the temporal orientation of tile time adverbials 
that modi\[y the tensed verb. 
Only a limited set of time adverbials can refer to 
present time. Indeed, the set is so small that it 
can be enumerated. The adverbials can be fhr- 
ther subclassified according to other times they 
may refer to. 
• only present (now, at the moment) 
• also past (just, German eben) 
• any time (toda35 this week, in the mean- 
time, tbr two weeks) 
All other time adverbials are incompatible with 
present time. 
(2) * On 19th November 2000, I sleep late. 
• Some adverbials only refer to past time (e.g. 
~stm'da35 last week, formerIL recentl), two 
days ago). 
(3) * I will be here yesterday. 
• Others can only be used with filturc time 
(tomorrow, next week, soon, in £our d~ys). 
2.2 Verbs Immune to Temporal 
Orientation Effects 
In some cases tile temporal orientation of adver- 
bials sounds a false alarm: Even though an ad- 
verbial requiring non-present syntactically mod- 
ifies the tensed verb, German present tense is 
translated as present (see examples (4) from 
the British National Corpus). The effect comes 
about because semantically the adverbial mod- 
ifies not the verb's eventuality but one of the 
verb's objects. 
712 
(4) a. 'lbmorrow i am ah'eady 1)lamfing a golf 
trip with the boss. (Verbmobi\] (:orlms) 
b. And w(" wish trim the very best of lu(:k 
tomorrow in Birminghmn. 
(British National Corpus, lINe) 
('. Another storm fl'om SE ... is expected 
here tomorrow. (BNC) 
The decisive factor seems to be the verb sense 
involved. Thus, for disambiguation a. list; of such 
'"il\[llll\[llte" vet'b senses ltlltSt be compiled. Such 
verbs can be modified by adverbials requiring 
1)r(~sent and adverbials requiring non-1)resent at 
the Sallle time. 
(5) am Montag haben wit jo%zt noch etwas Zeit 
011 ~/\]011(t~l.} r have we i~ow still some time 
but now we still have some time on Monday. 
2.3 Temt)oral Orientation and Scope 
Only the temporal orientation of wide-s(:ol)e 
adverbials is relevant for tense (lisambiguation 
(Butt, 1995). lrrequen(:y )tdverbials intercel)t 
the disambiguating etfe(:t (see (6)). It is (;here- 
fore imi)ortan(; to evaluate only those a(lvcr- 
bials that outs(:ope the fl'eqltelt(;y adverbial with 
widest scope. 
(6) a. John will be here on Monday. 
b. John is here on Monday every week. 
(:. John will |)e here in April every week. 
3 Simple or Progressive? 
A distinctive feature of the English tense system 
th',~t is missing in German is the differentiation 
be(,ween siml)le and t)rogressive aspect. We t'o- 
(:us here on 1;\]1(: usag(: of aspect in 1)r(:sent time. 
(7) present time -~ ,~'imple/)re,~'ent 
-+ l>rcs<mt t)rogres,vi~<'. 
3.1 Linguistic N~etors 
The factors involved have been thoroughly stud- 
ted and classitied in the linguistic literature 
(Greenbaum and Quirk, 1990). So we confine 
ourselves to a short re.view here. 
State Present. Stative verb senses get simple 
aspect. 
(8) a. • We are having a house on Oxtbrd 
Street;. 
b. We arc having dinner. 
Habitual Present. A habit is a set of <:vents 
of the same type. In semantic tern:s, a habit 
arises from quantiti('ation over events. If the 
events extend indefinitely into the past and fi:- 
ture., the lmbit is conceived as perutancu, t "and 
simple aspect is used; if the events occur over 
~ limited period of time, the habit is conceived 
as temporary and progressive aspect is appro- 
priate. A frequency adverbial can be used to 
speci\[y tit(: (relative) number of occurrences of 
the event. Ge.ncral .\[acts cml be viewed as a spe- 
cial type of a habit. They arc always expressed 
in simple asl)ect (see (9)). 
(9) Because water boils at 100°C, water is 
boiling at 100°C in the pot. 
Instantaneous Present. Dynamic verb 
senst~s that ret'er to a single event with little 
or no (lur~tion oceun'ing at the Sl)eech time 
are exl)ressed with simple aspect. This type 
of \])resent is used in commentm'ies (10a), 
self commentaries (10b) and with performative 
verbs (10c) referring to speech acts. 
(10) a. Joe scores a goal. 
b. I enclose an apt)lication tbrm. 
(:. For I)ermission to tmblish this paper, 
the authors l;tm.nk the l)el):~rtment of 
Economi(: Develol)ment. 
Durational Present. Dynamic verl) senses 
denoting an incomph:te event with dm'ation get 
progressive aspect. 
(11.) a. We are looking at; March sixteenth. 
(Verbmobil corpus) 
b. This is looking interesting. 
(Verbmobil corpus) 
3.2 Disambiguation 
State Present;. Disambiguation requires def- 
inition and classification of all relevant verb 
senses according to stativity. When in a first ap- 
1)roximation only the most fl'equent verb sense 
of each verb are considered, a list; of stative verbs 
can be extracted from a corpus. 
Habitual l?resent. The presence of a fie- 
quency adverbial points to a reading of Habitual 
Present. Since every event can be construed as 
a general fact, general facts arc very difficult to 
identify and will be disregarded. 
713 
Instantaneous Present. For disambiguation 
achievement verbs used in selfcommentm'ies 
and perfbrmative verbs need to be listed. 
Durational Present. Present events are usu- 
ally regarded as having duration, so progressive 
is the default aspect for dynamic verb senses in 
the present. 
4 Perfect or Not? 
In a special case, Germm~ present tense can be 
rendered as English present perfect: In English, 
perfect is used to describe periods that begin in 
the past and lend up to the present; German 
uses a non-perf~ctive tense in this situation. 
(1.2) Wir leben schon fiinf Jahre in Amsterdam. 
We live ah'eady five years in Amsterdam. 
We have lived in Amsterdam for five years. 
Whenever a period is described that begins be- 
fore and still holds at speedl time, a limitative 
time adverbial i is used. (This term is due to 
Bras (1.990).) This peculiarity makes disam- 
biguation very easy. 
(13) a. Er ist erst zwei Wochen hier. 
lie is onlyt two weeks here. 
He has only been here for two weeks. 
b. Er ist nur zwei Wochen hier. 
He is only two weeks hcxe. 
He is here for only two weeks. 
5 Definition of Granularity 
For our purposes we model the time axis as 
the set of rational 2 numbers Q. An interval 
is then a pair of rational nmnbers <s, c), such 
that s < e. The d'uration of an interval is the 
distance between start and end of the interval 
(d~Lr({s, c)) = e - s). On the interval structure 
we define the relations of inclusion (143) and 
overlap (14t)). 
(1.4) a. (81,c1} C (82, c2) +-} 82 ~.~ s1 A ~1 ~ (22 
b. @1,C1) 0 (82,('2) ~ 81 ~ (32 A 82 ~__ e 1 
1Limigal;ive adverbials go with the prepositions since 
mid for plus temporal measure nouns in English; in Ger- 
man they occur with the preposition seit and as duration 
adverbials modified by schon and erst. 
'~Although natural mmlbers could have been used to(), 
rational mm~bers are convenient since they allow free 
choice of the unit. 
5.1 Temporal nouns 
A temporal noun denotes a set; of intervals. We 
define the granularity of a temporal noun for- 
mally as a pair of numbers specifying the mini- 
real and maximal duration of its intervals (e.g. 
or'an(day) = (1., 1), gT(t,/~.(conference) = (1, 28), 
ora'n(senfinar) = (0.00138889, 334.812) if" the 
unit is a dw). The following relation is used 
to compare granularity values. 
(15) (d,tr~,durl) > {d'ur'~,dur~) +~ 
{dur'~,d'ur~) 7~ <&,r~,dur~> A dur I >> dur~ 
If 7t 1 has coarser grmmlarity than rt2, then an 
interval of rt:l cannot be included in aD. interval 
of' ~7,2. 
(16) ,,2: > -+ 
Vii ~ r~q,i,e c n2 : il g i2) 
Consider the fbllowing definition. 
(17) A telnporal noun n has t;11o property of 
disjoh~tness iff Vi~, i2 E n : ~il O i9 
Every calendar measure noun defines a partition 
on the time axis and has therefore the t)roperty 
of disjointness (e.g. hour, day, week, etelniti)O. 
Nouns functionally dependent on calendar mea- 
Sln'e l/ouns inherit the property (e.g. Monda35 
ChristlnaS, holida:B 6:45, ...). Event and state 
nouns have the disjointness property, if the de- 
scribed intervals fimctiolmlly depend on one of 
the particil)ants and the pm'ticil)allt is definite. 
Thus, example (18) is &wiant. 
(18) * Tomorrow at 6:30 Jones will give a talk 
at every conference. 
\]if ~zl has finer granularity than a noml ~z~ which 
has the property of disjointness, then every in- 
terval in r~,l overlaps with at most one interval 
in n2 (we disregard the case where il joins two 
intervals in n2). 
(19) V/;1 E ')'1: I{ ¢=: i', A ,:1 o ,:2 }1 -< 1 
5.2 Functions on Granularity 
Relational Nouns. Among the temporal re- 
lational nouns we distinguish nouns describing 
periods of definite length (e.g. quarter, t;hird, 
hall) f'ronl those that refer to periods of in- 
definite length (e.g. beginning, middle, end). 
In grmmlarity calculation, relational nouns con- 
tribute a factor. With relational nouns referring 
714 
l:o periods of indefinil;e, length we so.t; l;hc fact;or 
1 1;o ~-. 
Total)oral I)repositions. .letup n'al t)r(~i)osi- 
l;ions are mapl)c'd l;o inl;erva\] re, lal;ions. 
1. Some 1)rcl)osil;ions do not alter gramfl~ril;y 
(e.g. /;Cml)oral location on, in, at, duration 
during, throughout,/br). 
2. So:::(: pr(;posiCions des(:ril)c an oi)en-(md('d 
int;(;rval (e.g. bcibrc, at'tot, ti'om-ml, raM1). 
3. S()ln(; preposil;ions requir(; a. d(;t;ailed del:cr- 
minai;ion of i;oml)or;fl rcf(',rcn(:c, if t;hcy are 
l;o yieht granu\]a.ril;y t)r(;(li('fio:~s ((;.g. Hil~ce,, 
I)~'t;wc(;J 0 . 
To ('al(:ulaI;(, /~ramflaril;y wil;h i;h(' lal;t('a" l;w() 
('lass(;s, \re l;ak(; the grmmlmiI;y of I;h(; pr(;posi- 
I;ions' NP ~trgmncni;s as a guiddin< Th(; h('m'is- 
I:i(" asSmnl)l;ion is I;hat; if a, time adverbial is I;o 
d(,,signal;e a long period more (tel;nil is given in 
the NP a rguln(,nl;. TIHI,% l;h(', rcl(,.vanI; l;(;mpo- 
ral l)r('posil;ions map l;hc. n(mn gra.mflarii;y 1;o th('. 
n(',xl; higher level ()n a ccrI;~till Sca.lc (day nlonl;h 
year el;t,rnil;y). 
(':0) 1,efo,.(,, 6:; 0 
1)(Zore Monday (< inOlli;h or y('.a.r) 
b(~fore Monday, lsl: of ()(:l;ol)(,w (< year) 
1)('.for('. Monday, lst; of ()(:l;ol)cr 1998 
(infinite) 
Detcrmin(trs. Two (:lass(;s of dci;(;rmin('xs (:alJ 
t)e disl;inguis\]md: Sl)(;(-ifi(: ((lolinil;(; or ind(:linil;(;) 
~md qua,nl;iti(:a.l;ional (Ka.m t) and l/(;yh',, 1993). 
Sp(x'ific d(;l;(;rmin(;rs (to noI: (:hang(: gra:mla.rit;y. 
Q tmnl;ifi(;rs, how('ver, ('.xt('.n(l gramila.ril;y if il; is 
('lem" l;\]mt, ovc.ry inl:(;rval (l(:noi;c.d 1)y a. tX'ml)oral 
noun occurs only on(:(' wil;hin a. (:(;rl;ain l)eriod. 
(21) Mo,,d., y (,v(;(,,k) 
(;v('a'y beginning of a (;olff(~'r(!nc(; ((:onf:'renc('O 
O,V(:l'y bimont;hly m(;cl;ing (two monl;hs) 
BUT: (;very qum't;e,r of a y(;ax" (ttu'c(: 
months, nol; year) 
Appositions. If temporal nouns form ~t (:on- 
sl;ituent ((;.g. yo.vtcrday nt'tcrl~oo.u), the gram:- 
\]a:dl;y of the. head noun is (:hosc, n (tyl)i(:ally l;his is 
l;h(, filw.r gra.nularity). Sill(:(; ini;(;rwds arc usually 
descril)oxt Oll S()llrC(. ~ }/,lid (;}/,l'g(;l; side, granularii;y 
iI~\[brInal;ion of \])oth source and l;arg(;t tOtal)oral 
nouns can 1)(, exl)loil;cd to achieve higher preci- 
sion (e.g. Vormittag. morning). 
6 Scope Resolution 
For tens(', disamtfigua,tion scope re,solul;ion of 
|;ime adverbials can l)e crucial (cf. st',ctfion 2.3). 
6.1. I,Smctional Concepts 
Functional conc(;i)ts resta'icl; the t)ossibilit;ies of 
scope r('.solul;ion (Alshawi, 1992). 
A quant;ificr Q(x,/2., S) is iterative iff it requires 
l;h&t; con('o.t)i;u}fl klmv, q(~.dgc allows for al; h;asI; 
l;wo ol)j(,.cl;s in the interse.cl, ion of il;s rcsl;ric- 
t:i,,,, ,md(,a,' s (1{ :'; : A 
S(x) }1 > \]). Ex~mqfl(;s t:br it;ea'~l;ivc qumlt, i- 
ti(;rs m'c eve,35 most, scvcra\] and l;hc distrilml;ive 
re~(liltg of phn'al. 
A conccl)t; (_7 is funct;iomd on doma,in D and 
r',mgc \]eitl:'V:,: : 19(:~:) -+ I{Y: W(y)AO(x,y)}\[ < 
1 (e.g. every human has exactly one faA;hc.r). 
ll; can b(; shown thai; if an itc'ral;ive qua nl;ifier 
qua.ni;iii('.~ over i;h(' range of a funcl;iona\] concepi;, 
il; musl; oul;sCOl)e. I;he dom a.in quantifier (e.g. m .... 
c W t?~thcr oul;s('opt',s a. stude,ut; in r'veW ti~thc,': ()f 
a .'-,'tlldcut) (Moran and lk,r(;ira, 1992). 
'li;mporal ov(',rlap is a fllncl;ional conc(;pl; if the 
donmin inl;('.rva\] has Iin(,.r gramlla\]'il;y t;h;m l:he 
rm, ge inlx;,'va.l (see (19)). Ih'.ncc', if l;wo time 
a dvert,ials 'n,i (on Monday in (22)) and n2 (c'veW 
u'ec'k in (22)) modify the same ev(!nl;, nl has 
liner gramflm'il;y l;han '/~,2, and r~,2 is il;(;ral;iv('ly 
(tuanl;ificd, i;h(m ~*,2 Illll,ql; outs(:op(; hi. 
(22) .lotto visil;ed .lane every w(!('k on Monday. 
6.2 Temporal Quantification 
Temporal quanl;ificatioll has a curious i)roi)(;rty. 
Prcl)o,~il;iona\] t)hrases are gonel'ally l;real;(',d as 
inWrsc('l;ive modifiers to the head insl;m:c('. (AI- 
sh~uvi, 1.992). II:' we analyse sent;on(:(; (23~) i. 
l;his v(:in, w(; gel; (231)) as h)gical r(;1)rescntat;ion: 
The des('ribcd evenl;s arc situal;ed in May and in 
()V(}l'y x, VO, Ok. 
(23) a. In May John visited ,Jmm (:very wed(. 
1,. ?,,,: a v,,,, : ,,,(,(,k(,,,) 
visit(c, John, .lmm) A c C. 'm, A (' C 'u; 
On closer insl)ecl;ion wc s(;(; thal; I;h(; repr(;s(;ni;a- 
l;ion is (:Ollla'adictory. Take an arbil;rary week, 
say in April. Tlw.n I;he fornmla ass(;rts that 
t, her(; is a visit; in thi,q w(,ek (i.(;. in April) and 
715 
ill May, which is inconsistent. Thus, the for- 
mula should not quantify over weeks in general 
but over weeks in May: An inclusion restric- 
tion to the wide-scope adverbial is needed in 
the narrow-scope adverbial (Kamp and Reyle, 
1993). 
(24) ~m: May(rr~) A Vw: week(w) A w C rn, 
~e : visit(e, John, Jane) A e C m A e C_ w 
Since temporal quantification requires that a 
narrow-scope iterative adverbial be included 
in the wide-scope adverbial, configurations are 
excluded where by conceptual knowledge the 
narrow-scope adverbial al cannot be included in 
the wide-scope adverbial a2. By theorem (16) 
this is the case if a,i has coarser granularity 
than a2. 
6.3 Granularity and Scope 
We have now seen two nlotivations for the prin- 
ciple (25). 
(25) If ~,~ has finer granularity than r~2 and rt,2 
is iteratively quantified, ~,1 camot have 
scope over ~t2. 
Let us now consider the tbllowing t)rinciple: 
(26) If 7/'1 has finer granulm'ity than 7~,,) and r~,l 
is iteratiwfly quantified, ~zl cmmot have 
scope over ?~,2. 
We are not in a position to tbrmally explain the 
principle. It, holds for at least all nouns with 
the disjointness property. Although in exam- 
ple (27a) the vq reading would make perfect 
sense (Jones is always on holiday), it is excluded. 
In contrast, example (27b) allows this reading 
(.Jones shuttles between conference sites). The 
principle is not restricted to temporal grmmlar- 
ity: In (27c) the V~ reading is excluded, too. 
(27) a. Every Monday, Jones was here in a 
month in which he was on holiday. 
b. Every afternoon, Jones gave a talk at a 
conference. 
c. On every page, 1%und something in- 
teresting in a paper I read. 
Taken together, the two principles assert that 
the grmmlarity ranking determines the scope or- 
der. In the dismnbiguation algorithm presented 
in section 7 we are mainly interested in the po- 
sition of the highest (iterative) quantifier. So if 
every pair of time adverbials can be compared 
in terms of granularity, we have a procedure to 
compute this position. Comparison of granular- 
ity (1.5) is not defined if the granularity values 
overlap or m'e equal. Equal granularity is only 
possible with specific time adverbials. 
(28) • John came from every Wednesday to ev- 
ery weekend 
Other heuristics will have to come into play in 
case of overlapping granularity (see section 8 for 
further discussion). 
6.4 Deictic Adverbials 
Another factor for determining scope order is 
deixis. Some adverbials ~tre connected in their 
interpretation to the time of speedl (now, at the 
moment, next week, last week). Since time of 
speech is deictic (it depends on the context of 
utterance), hence defilfite, every function on it 
will also be definite. Deictic adverbials always 
get wide-scope position. 
Sentences in which deixis conflicts with granu- 
larity m'e deviant. 
(29) • Next month, I will be here every year. 
7 The Disambiguation Algorithm 
In the implementation, an underspecified se- 
nlant;ie representation formalism is used to en- 
code the source analysis and the transfer result 
for the target (the Verbmobil Interface Term 
(FIT) formalism (Bos el; al., 1998), which is 
based on the theory of Underspecified Discourse 
Representation Structures (Ileyle, 1995)). The 
disambiguation heuristics of the system com- 
pletely rely on local context. The most impor- 
tant features in local context are source tense, 
the predicate names of the tensed verb in source 
mid target, and the time adverbials inodifying 
the verb in source and target (Sdfiehlen, 1998). 
In a first step, the source and target representa- 
tions are converted into an abstract representa- 
tion, using the VIT transfer forlnalism (Dorna 
and Emele, 1996). All information irrelevant 
to tense resolution is removed. Since no full- 
fledged tense logic is implemented, information 
about temporal reference is discarded as well. 
Temporal adverbs are decomposed into prepo- 
sitional phrases (e.g. .yesterday -+ on a past, 
716 
day). In particular the following featm'es are 
extracted: 
(30) a. multiple classification of verb senses 
• stative or dynamic (for English 
only, cf. section 3.2) 
• 1)otentially pertbrmative/self- 
colnmentary or not (for English 
only, cf. section 3.2) 
• "immune" or not (cf. section 2.2) 
b. temporal relation expressed by preI)o- 
sitions 
e. temt)oral orientation of pret)ositions 
(on Monday), adjectives (the previ- 
ous Monda:v) and determiners (this 
Monday) (of. section 2.1) 
d. granularity of nouns and adverbs (e.g. 
Cerma,) g ,,, ti gig (,,,ho>-(l<,j)) 
e. classification of determiners (quantiti- 
cational/specitic/alnbiguous) 
f. classification of adverbs (frequency ad- 
verb or not) 
We now give an outline of the disambiguatixm 
algorithm for translating German t)resent. It is 
(:lear l;hat the algorithln is \]mm'isti(" in lllglJxy Hs- 
t)ects, but in the absence of Colltext alld (lel;aile, d 
discourse anMysis it does not seem possible to 
do much better. 
1. For every tensed verb, determine all time 
adverbials modii~ying it and collect them in 
the set TA. 
2. Order the tinle adverbials in TA according 
to scope (of. section 6). 
3. Let STA be the set; of all specitic time ad- 
verbials in 5/'A (i.e. adverbials denoting a 
specific interval) not in the scope of a quan- 
tificational adverbial or frequency adverb 
(cf. section 2.3). 
4. Perfect or Not? (cf. section 4) 
If one of the time adverbials in ETA is con- 
nected to the tensed verb over a linfitative 
relation, choose perfect; else choose non- 
t)erf'ective tense. 
5. Present or Future? (cf. section 2) 
Choose present if the verb is "immune" to 
temi)oral orientation (cf. section 2.2). Else 
unify the temporal orientation contributed 
by the time adverbials in ETA. In case the 
result excludes present time, choose fltture; 
else choose present (cf. section 2.1). 
6. Simple or Progressive Aspect? (of. sec- 
tion 3) 
(a) If the tensed verb has a stative sense, 
choose simple (State Present). 
(b) If the tensed verb is used in a self- 
commentary or perfonnatively, choose 
simple (Ilxstantaneous Present). 
(c) If there is an adverbial ill STA, choose 
progressive (Temporary Habit and Du- 
rational Present). 
(d) If there is a quantificational adverbial 
or flequency adverb in TA, choose sim- 
ple (Permmmnt Habit). 
(e) Else choose progressive (Durational 
Present). 
8 Results 
We tested the system on a data base of 13,625 
pairs of Gernlan VI~I\]q with their English trans- 
lations, containing 12,036 tensed verbs. All 
the d~tl;a were in the appointment schedul- 
ing domain which is investigated in Verbmobil. 
They wore transliter~ted and syntactically an- 
notated 1)3; hand. rlk'anslation was perforined by 
the Verbmol)il transfer component (Dorna and 
Emele, 1996). 2,758 tensed verbs were modified 
by time. adverbiMs, 1,373 of these verbs were 
modified by time adverbials with known granu- 
larity. 
The algorithm made the tbllowing choices tbr 
these data. The second column shows the total 
number of tensed verbs, the third column only 
counts those modified by time adverbials with 
granularity. 
-Perfect 0 0 
Future 729 729 
State or Instax)taneou8 Presenl 8,782 516 
Permanent Habit 29 29 
Dynalnic Present 2,496 99 
The described algorithm only inspects linguistic 
factors. Doxnain-specific information could po- 
tentially improve results. In the Verbmobil do- 
main e.g. several event types do not hal)i)en in 
717 
the present but only in the fllture (tra.vc\], meet, 
eat, ...). 
1,1 93.6% of the cases a specific wide-scope time 
adverbial could be determined with gramflarity 
constraints. In 4.7% of the cases several time 
adverbials of equal granularity had wide scope. 
A good deal of these cases were alignment er- 
rors with the translations (e.g. iibel"morgen - 
the day after tomorrow). Other cases were due 
to the lack of a treatment for coordination (e.g. 
on Monday aud on Thmwday or ti'om June to 
August). Some cases were genuine double de- 
scriptions of days: 
(31) a. Is it possible for you tomorrow on the 
second? 
b. I would have time on Wednesdw on 
Wednesday the third of May. 
In 1.7% of the eases the wide-scope adverbial 
could not be determined because some a.dver- 
bials had overlapping gralmlarity values. Here 
the main culprit was the unspecified adverb 
when (see (32a)). Other cases were due to in- 
correct preposition attachment (see (321,)). 
(32) a. When shall we meet on Mond~y? Next 
week/6:30. 
b. Would you be available in the time pe- 
riod until June? 
9 Summary 
The pal/er has presented a disambiguation algo- 
rithm ibr translation of German present into En- 
glish. After a discussion of the factors involved, 
particular emphasis was placed on an account 
of scope resolution among time adverbials. It 
has been shown that grmmhu'ity calculations go 
a long way towards the goal of full scope resolu- 
tioii. The cross-commotions between granular- 
ity and scope have been analysed in detail, and 
some motivation for these connections has been 
given. 
One area of future work is to apply the model to 
larger corpora and extend it to cover the full set 
of tenses. If translations can be aligned with the 
training data, it would be interesting to investi- 
gate the extent to which the model can be used 
to extract (parts of) the pertinent granularity 
information on temporal nouns from the corpus 
(Schiehlen, 1998). For example, the occurrence 
of a configuration like (33) could be interpreted 
as evidence tbr NOUN having coarser granular- 
ity than week. 
(33) FUTUIT{E-EVENT every week in NOUN 

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