136 T ansla o s’ Resou ce Dominance and he Success o Finding
he Ta ge Te ms in Human T ansla ion and Pos -edi ing o
Machine T ansla ion
Esz e Se mann
Má a Lesznyák
doi.o g/10.35321/ e m31-07
T ansla o s’ Resou ce Dominance and he
Success o Finding he Ta ge Te ms in
Human T ansla ion and Pos -edi ing o
Machine T ansla ion
Ve ėjų iš eklių domina imas i sėkminga e imo
kalbos e minų paieška e čian žmogui a ba
pos edaguojan mašininį e imą
ESZTER SERMANN
Depa men o I alian Language and Li e a u e, Uni e si y o Szeged, Hunga y
ORCID id: h ps://o cid.o g/0000-0001-8753-5312
MÁRTA LESZNYÁK
Ins i u e o English and Ame ican S udies, Uni e si y o Szeged, Hunga y
ORCID id: h ps://o cid.o g/0000-0002-9354-0633
ABSTRACT
This s udy p esen s he i s esul s o p ocess-o ien ed esea ch on he ypes o on-
line ansla ion esou ces used by i s - and second-yea ansla ion ainees when
ansla ing and pos -edi ing a legal ex om English in o Hunga ian. Based on he
sc een eco dings o he s uden s’ wo k low, he possible ela ions be ween esou ce
dominance ( e mino-lexicog aphic o ex -based), ime on ask and he success o
inding he co ec a ge e ms we e analysed. Ou esul s indica e ha s uden s
gene ally p e e e mino-lexicog aphic sou ces o ex -based sou ces. In e es ingly,
in mos cases, he success o inding he co ec a ge e ms showed no signi ican
co ela ions ei he wi h ime on ask o wi h esou ce dominance. The only excep-
ion was he pos -edi o g oup, whe e he e was a signi ican co ela ion be ween
he equency o using ex -based sou ces and he success o inding co ec e ms.
In addi ion, e idence was ound ha pos -edi o s wo ked mo e e icien ly han
om-sc a ch human ansla o s in e ms o ime and sea ch e o . The pape ends
wi h possible explana ions o he indings and sugges ions o ansla o aining.
KEYWORDS: ansla ion, pos -edi ing, ansla ion p ocess esea ch, ansla ion esou ces,
adequacy o e minology.
137Te minologija | 2024 | 31
ANOTACIJA
Šiame y ime pa eikiami pi mieji į e imo p ocesą o ien uo o y imo apie in-
e ne inių e imo iš eklių ipus, ku iuos naudoja pi mo i an o ku so e ėjai
p ak ikan ai, e sdami eisinį eks ą iš anglų kalbos į eng ų kalbą i jį pos -
edaguodami, ezul a ai. Remian is s uden ų da bo eigos ek ano į ašais, bu o
analizuojami galimi yšiai a p iš eklių ( e minog a inių i leksikog a inių (angl.
e mino-lexicog aphic) a eks inių) domina imo, užduočiai ski o laiko i sėkmin-
go eisingų e imo kalbos e minų adimo. Mūsų ezul a ai odo, kad s uden-
ai dažniausiai eikia pi menybę e minog a iniams i leksikog a iniams, o ne
eks iniams šal iniams. Įdomu ai, kad daugeliu a ejų eisingų e imo kalbos
e minų sėkmingas su adimas nepa odė eikšmingos ko eliacijos nei su užduočiai
ski u laiku, nei su iš eklių domina imu. Vienin elė išim is bu o pos edak o ių
g upė – nus a y as eikšmingas yšys a p eks inių šal inių naudojimo dažnumo
i sėkmingo eisingų e imo kalbos e minų adimo. Be o, nus a y a, kad pos -
edak o iai di bo e ek y iau nei e ėjai p ak ikan ai iek laiko, iek i e imo
kalbos e minų paieškos pas angų a ž ilgiu. S aipsnis baigiamas galimais y imo
ezul a ų paaiškinimais i pasiūlymais dėl e ėjų mokymo.
ESMINIAI ŽODŽIAI: e imas, pos edaga imas, e imo p oceso y imas, e imo iš ekliai,
e minijos inkamumas.
1. INTRODUCTION
T ansla ion ools ha e changed adically o e he las wo decades, wi h
online digi al esou ces almos comple ely eplacing pape -based ools.
In oday’s echnological en i onmen , many online digi al esou ces a e
a ailable o ansla o s, bu choosing eliable and e ec i e ools equi es
ca e and ou ine. Resea ch has con i med ha he use o online ansla ion
esou ces cons i u es a signi ican p opo ion o he o e all ime spen on
ansla ion (H elplund 2017); mo eo e , cons an echnological changes
ha e led o an inc eased in e es in he ypes o ansla ion esou ces and
hei use in he p ocess o human ansla ion and pos -edi ing o machine
ansla ion (e.g. Gough 2019; H elplund 2016, 2017; P ie o Ramos 2021).
In ecen yea s, pos -edi ing o machine ansla ion has become a common
p ac ice o ansla o s, bu one o he majo sho comings o machine
ansla ion engines is ha hey p oduce a high numbe o e minological
e o s and inconsis encies, so pos -edi o s mus check he co ec ness and
consis ency o a ge language equi alen s, which is also a ime-consum-
ing p ocess equi ing a high deg ee o p ecision.
The esea ch p esen ed he e ocused on de e mining wha esou ces
ansla ion ainees p e e when ansla ing o pos -edi ing a legal ex , and
138 T ansla o s’ Resou ce Dominance and he Success o Finding
he Ta ge Te ms in Human T ansla ion and Pos -edi ing o
Machine T ansla ion
Esz e Se mann
Má a Lesznyák
how esou ce use dominance is linked o pe o mance indices like ime on
ask and co ec e minology use. Fi s , a b ie li e a u e e iew is p o ided
ocusing on ansla ion p ocess esea ch, online ansla ion esou ces and
ansla ion-o ien ed esea ch ac i i y. Nex , he Szeged T ansla ion Com-
pe ence esea ch p ojec is desc ibed, and he me hodology o he p esen
in es iga ion is de ailed. This is ollowed by he p esen a ion and discus-
sion o he esul s and a conclusion.
2. LITERATURE REVIEW
2.1. T ansla ion P ocess Resea ch (TPR)
T ansla ion p ocess esea ch began o p oli e a e in he 1980s (Ká oly 2022;
Lesznyák 2024) when esea che s u ned hei a en ion o he cogni i e,
psychological and beha iou al aspec s o ansla ion. Ea ly p ocess-o ien -
ed esea ch ocused on ansla ion compe ence and he de elopmen o
esea ch me hods (e.g. Wilss 1988; Ti kkonen-Condi , Jääskeläinen 2000).
In he 21s cen u y, echnological ad ances ha e b ough adical changes
no only o ansla ion p ac ice, bu also o ansla ion esea ch (see Klau-
dy 2022 o mo e de ails), including new esea ch ools and me hods on,
among o he hings, he psychological ac o s o ansla ion (Angelone
2010), ansla ion s a egies, ansla o beha iou (D ags ed 2005; Lesznyák
2008), pedagogical issues in ansla ion (Sh e e 2006; E icsson 2010), he
p ocess o simul aneous ansla ion (Seebe 2015), and he physical en i-
onmen o ansla o s (Eh ensbe ge -Dow, Hunzike Heeb 2016).
In ansla ion p ocess esea ch, schola s use he ollowing me hods o
obse e ansla o s: hink-aloud (TAP), keys oke logging, sc een eco d-
ing, eye- acking, e ospec i e in e iews, and di ec obse a ion o he
ansla ion p ocess (Risku 2019; Ká oly 2022; Lesznyák 2024), and hen
y o iden i y he egula i ies ela ed o he ansla ion p ocess. TPR is
usually no indi idual esea ch, as da a collec ion and analysis equi e
collabo a i e wo k (Risku 2019), and quan i a i e and quali a i e me hods
a e o en combined.
2.2. The use o ansla ion esou ces as an elemen o ansla ion compe ence
Types and use o ansla ion esou ces, cogni i e e o , and pa e ns o in-
e ac ion be ween p o essional ansla o s and online esou ces a e widely
s udied opics (Gough 2018; Lesznyák 2008; H elplund 2016, 2017; P ie-
o Ramos 2021 e c.). Di e en classi ica ions o ansla ion esou ces can
139Te minologija | 2024 | 31
be ound in he e minological and lexicog aphical li e a u e (Fó is 2019;
Gaál 2016; Se mann 2021; Tamás 2014).
The skills ela ed o he use o ansla ion esou ces a e included – ei-
he explici ly o implici ly – in he di e en models o ansla ion com-
pe ence. The PACTE Resea ch G oup (Hu ado Albi 2017) classi ies he
use o esou ces as an ins umen al sub-compe ence, while in he la es
e sion o he EMT model (2022), in o ma ion mining compe ence does
no appea as a sepa a e elemen , bu he co ec use o sea ch engines
and he use o co pus-based esou ces a e included in echnological com-
pe ence. The T ansCe model (Budin e al. 2013) includes in o ma ion
mining and echnological compe ence, while he eT ansFai model (2016)
includes in o ma ion e ie al and e minology compe ence. In summa y,
he e ec i e use o ansla ion esou ces plays a ole in some o m in each
o he ansla ion compe ence models examined.
2.3 T ansla ion-o ien ed esea ch ac i i y (TRA)
We based ou s udy on H elplund’s esea ch abou ansla o s’ use o digi al
esou ces du ing ansla ion (H elplund 2016, 2017) and Gough’s esea ch
abou ansla ion-o ien ed esea ch ac i i y (Gough 2016, 2018, 2019, 2023).
H elplund’s indings (2017) show ha digi al esou ce consul a ion cons i-
u es a conside able amoun o he o e all ansla ion ask ime (20 pe cen ),
and ansla o s mos ly used gene al language dic iona ies, bilingual dic io-
na ies and In e ne sea ch engines o bo h li e a y and echnical ansla ion.
Gough (2019) used a quasi-na u alis ic, obse a ional me hod ia sc een e-
co dings o s udy p o essional ansla o s’ esea ch ac i i y. The au ho iden-
i ied ou esou ce beha iou ypes: Dic iona y En husias , Pa allel Tex
Fan, Mixed Use and MT Adop e . He esul s sugges ha domain expe ise
o a lack o i plays a ole in he esou ce beha iou p o ile.
In a p e ious s udy, we in es iga ed he ypes o online ansla ion e-
sou ces used by i s - and second-yea s uden s en olled in a Mas e o
T ansla ion and In e p e ing p og amme when ansla ing and pos -edi ing
he same legal ex om English in o Hunga ian. Resul s show ha i s -
yea s uden s we e mo e likely o use monolingual and bilingual dic io-
na ies, while second-yea s uden s op ed o mo e co pus-based esou ces.
The choice o he online ansla ion esou ces was no de e mined by he
mode o ansla ion (HT o PE), bu by he ansla o ’s le el o expe ise
(Se mann 2023).
140 T ansla o s’ Resou ce Dominance and he Success o Finding
he Ta ge Te ms in Human T ansla ion and Pos -edi ing o
Machine T ansla ion
Esz e Se mann
Má a Lesznyák
In he p esen s udy, based on he sc een ideos o s uden s’ wo k low,
we ied o ind co ela ions be ween ansla o ainees’ esou ce domi-
nance, he ime on ask and he success o inding he co ec a ge e ms.
Resou ce dominance was ope a ionalized as he numbe o he ypes o
di e en esou ces used and he equency o consul ing hese sou ces,
which led o wo ca ego ies: (a) e mino-lexicog aphic and (b) ex -based.
3. THE SZEGED TRANSLATION COMPETENCE
RESEARCH PROJECT – AIMS AND OBJECTIVES
The esea ch epo ed he e is pa o he T ansla ion and MT Pos -Edi -
ing Compe ence Resea ch Cen e’s o e a ching esea ch p ojec (Uni e -
si y o Szeged, Hunga y), which aims o in es iga e he ole ha elemen s
o ansla ion compe ence (PACTE) play in human ansla ion and he
pos -edi ing o machine ansla ion. In he p ojec , we ha e been wo king
wi h he a iables o sou ce language skills (English), L1/ a ge language
(Hunga ian) compe ence, p o essional backg ound knowledge ela ed o
he con en o he sou ce ex (bilingualism, copy igh ), decla a i e knowl-
edge o ansla ion, he sou ce language ex ype, ansla ion expe ience,
wo k mode (HT o PE), and s uden s’ pe cep ions o he ad an ages and
disad an ages o wo king wi h each me hod (Lesznyák, Bak i, Se mann
2023, 2024). Ha ing been in ol ed in p oduc -o ien ed esea ch, we a e
now p esen ing he i s esul s o ou ansla ion p ocess esea ch.
In he in es iga ion epo ed he e, ou esea ch ques ions we e he ol-
lowing:
1. Wha a e he esou ce p e e ences o he di e en subg oups (1s
and 2nd yea s uden s, HT and PE s uden s)?
2. How is s uden s’ esou ce dominance ela ed o he success o ind-
ing he a ge equi alen s o he key e ms?
3. Is he e a co ela ion be ween esou ce dominance and ime on ask?
4. Is he e a co ela ion be ween he success o inding he co ec
a ge e ms and ime on ask?
4. METHODOLOGY
4.1. Pa icipan s and ma e ial
14 i s -yea s uden s (a he beginning o hei s udies) and 12 second-yea
mas e ’s s uden s o ansla ion (a he end o hei s udies) o med he sam-
ple o he p esen s udy. I is impo an o s ess he e ha a he Uni e si y

141Te minologija | 2024 | 31
o Szeged, in Hunga y, ansla o aining akes place a he mas e ’s le el
exclusi ely, wi hin he amewo k o a ou -semes e ansla o and in e -
p e e aining p og am. The e o e, i s -yea mas e ’s s uden s could be
iewed as highly skilled language lea ne s o use s wi h no p io ansla-
ion expe ience. Addi ionally, i ’s wo h no ing ha he s uden s did no
ecei e any speci ic aining in pos -edi ing a he ime he da a was col-
lec ed, bu second-yea s uden s had al eady comple ed he cou ses ‘Basics
o Law’ and ‘Legal T ansla ion’.
The sample was di ided in o wo subg oups ( ansla o o pos -edi o ),
and hey we e asked o ansla e o pos -edi a 350-wo d long legal ex (a
pa o a copy igh ag eemen , see Appendix). The sou ce language was
English, he a ge language was Hunga ian and English was he B o C
language o he ansla o ainees, and Hunga ian was hei A language.
The MT ou pu o he pos -edi o s was p oduced by eT ansla ion, he ma-
chine ansla ion ool o he EU.
4.2. The da a collec ion p ocedu e
Da a collec ion ook place in Au umn 2022 and in Sp ing 2022. All he
ansla ions we e p epa ed in a class oom se ing, and he e was a ime
limi o 120 minu es o he ask, bu ha limi was ne e ac ually eached.
S uden s had in e ne access and we e allowed o use wha e e sou ces and
web pages hey wan ed o use. Ne e heless, s uden s in he HT condi ion
we e ins uc ed o e ain om MT. S uden s we e asked o p oduce a a ge
ex o publishable quali y (i.e., ull pos -edi ing o he MT ou pu ), wi h-
ou using TM so wa e. S uden s wo ked in T anslog, as da a was collec ed
on he ansla ion/pos -edi ing p ocess, oo. In addi ion, OBS S udio was
used o eco d he compu e sc een while s uden s we e wo king on he
ansla ion/pos -edi ing ask. To es ablish ime on ask, ideo eco dings
we e used. The leng h o he ansla ion/pos -edi ing p ocess was coun ed
om he momen he ‘s a logging’ bu on was pushed in T anslog un il
he ‘s op logging’ bu on was pushed. Because o a echnical b eakdown,
some da a was los , as a esul , we could use 22 eco dings in o al.
4.3. Me hods o da a analysis
Based on he sc een ideos o s uden s’ wo k low, measu es on esou ce
use we e c ea ed. Fi s , each esou ce s uden s consul ed was ca ego ized
ei he as e mino-lexicog aphic (LEX) o as ex -based (TXT). Wi hin
142 T ansla o s’ Resou ce Dominance and he Success o Finding
he Ta ge Te ms in Human T ansla ion and Pos -edi ing o
Machine T ansla ion
Esz e Se mann
Má a Lesznyák
each g oup wo ca ego ies we e c ea ed: (1) he numbe o he speci ic
ypes o esou ces used (e.g. 3 dic iona ies) and (2) he o al equency o
consul ing hese sou ces (e.g. 11 sea ches /in he 3 dic iona ies). This way
ou a iables we e c ea ed ha we e used in he quan i a i e analysis:
LEX numbe , LEX equency, TXT numbe , and TXT equency.
A e wa ds, 10 key e ms we e selec ed om he sou ce ex (see Ap-
pendix), and hei equi alen s we e e alua ed in he a ge ex s, which
we e ansla ed o pos -edi ed by he s uden s. Se en o he e ms belong
o he legal domain and h ee o hem o he academic domain. The co -
ec Hunga ian equi alen s o he legal e ms we e de e mined by an ex-
pe in copy igh law.
Fo he s a is ical analysis, SPSS . 26 was used. The analysis ocused
on de e mining he esou ce dominance o he subg oups wi h he help
o pai ed samples - es s, compa ing he esou ce dominance o di e en
subg oups wi h independen samples - es s, and we also ied o ind co -
ela ions be ween esou ce dominance, success in inding app op ia e e -
minology and ime on ask. Because o space es ic ions, we will e ain
om sha ing la ge amoun s o da a wi h non-signi ican esul s and will
ocus on signi ican indings.
5. RESULTS
5.1. Di e ences in esou ce dominance wi hin he subsamples
Ou i s esea ch ques ion aimed a inding ou wha ype o esou ces he
di e en subg oups p e e ed. Fi s , pai ed samples - es s we e ca ied ou
o compa e he p e e ences wi hin he i s -yea and second-yea samples.
On he one hand, we compa ed how many di e en ypes o esou ces hey
used, and on he o he hand, he equency o consul ing hese esou ces
was con as ed.
Wi hin he i s -yea sample (n = 12), i was ound ha s uden s used
signi ican ly mo e e mino-lexicog aphic (M = 2.42, SD = 1.68) han
ex -based esou ces (M = 1.33, SD = 1.23, (11) = 3.463, p = .005). In
line wi h his, hey also did signi ican ly mo e sea ches in e mino-lexi-
cog aphic (M = 18.00, SD = 13.86) han is ex -based sou ces (M = 5.17,
SD = 5.80, (11)= 3.736, p = .001).
In he second-yea sample (n = 10), no signi ican di e ences we e ound
in he ypes o sou ces used by he s uden s ( e mino-lexicog aphic M =
1.90, SD = 0.74, ex -based M = 1.40, SD = 1.27, (9) = 1.246, p = .244).
143Te minologija | 2024 | 31
In o he wo ds, he e mino-lexicog aphic and ex -based sou ces we e
used o app oxima ely he same ex en , and he mino di e ence in mean
alues may be due o measu emen e o . Howe e , analysing he equency
o sea ches has shown ha second-yea s uden s, jus like hei i s -yea
pee s, we e engaged in a signi ican ly highe numbe o e mino-lexico-
g aphic sea ches (M = 17.2, SD = 11.10) han in ex -based sea ches (M =
5.4, SD = 5.83, (9) = 3.190, p = .011). As can be seen, he s anda d de i-
a ion o ex -based sea ches was highe han he mean, which is a signal
o high a ia ion in and abno mal dis ibu ion o he da a. Consequen ly,
medians we e also compa ed o he equency o sea ches. The pai ed sam-
ples Wilcoxon- es showed ha he medians we e signi ican ly di e en ,
oo, wi h he e ec size being la ge ( e mino-lexicog aphic MDN = 14.50,
ex -based MDN = 3.50, Z (9) = -2.497, p = .013, = 0.79).
In he nex s ep, he sample was di ided in o human ansla o s and
pos -edi o s, and esou ce p e e ences we e analysed wi h pai ed samples
- es s once again. In he human ansla o g oup (n = 10) no signi ican
di e ence was ound be ween he numbe o he wo ypes o esou ces used
( e mino-lexicog aphic M = 2.70, SD = 1.16, ex -based M = 1.90, SD =
0.99, (9) = 1.809, p = .104). Ne e heless, igu es showed ha s uden s did
signi ican ly mo e sea ches in e mino-lexicog aphic (M= 27.8, SD = 9.36)
han in ex -based sou ces (M = 8.5, SD = 5.87, (9) = 4.636, p= .001).
Resul s o he - es s indica ed ha he pos -edi o s used signi ican ly
mo e e mino-lexicog aphic (M = 1.75, SD = 1.36) han ex -based esou c-
es (M = 0.92, SD = 1.24, (11) = 2.802, p = .017). As he s anda d de ia ion
o ex -based sou ces was la ge han he mean indica ing abno mal dis i-
bu ion, he pai ed samples Wilcoxon- es was used o compa e he medians.
The es esul s showed ha he e was a signi ican di e ence be ween he
medians, al hough he p obabili y o measu emen e o was sligh ly highe
( e mino-lexicog aphic MDN = 2, ex -based MDN = 0, Z(11) = -2.226,
p = .026, = 0.643), bu he e ec size was s ill mode a e o s ong.
The pai ed samples - es showed ha pos -edi o s ca ied ou signi i-
can ly mo e sea ches in e mino-lexicog aphic (M = 9.17, SD = 7.03) han
in ex -based sou ces (M = 2.58, SD = 3.99, (11) = 4.026, p = .011). Be-
cause o abno mal dis ibu ion, he pai ed samples Wilcoxon- es was ap-
plied again, o check whe he medians we e signi ican ly di e en . Resul s
o he es s we e signi ican again, sugges ing ha he di e ence be ween he
median numbe o sea ches in e mino-lexicog aphic sou ces (MDN = 8)
144 T ansla o s’ Resou ce Dominance and he Success o Finding
he Ta ge Te ms in Human T ansla ion and Pos -edi ing o
Machine T ansla ion
Esz e Se mann
Má a Lesznyák
and in ex -based sou ces (MDN = 0) is signi ican ly di e en (Z(11) = - 2.805,
p = .005, = 0.810) wi h he e ec size being la ge.
5.2. Resou ce dominance di e ences be ween he subsamples
A e cha ac e izing he indi idual subsamples, we compa ed he g oups,
ha is, i s -yea and second-yea s uden s, on he one hand, and human
ansla o s and pos -edi o s, on he o he hand, wi h each o he . No signi -
ican di e ences we e ound be ween i s -yea and second-yea s uden s’
esea ch ac i i ies on ei he o he measu es.
Howe e , when human ansla o s and pos -edi o s we e compa ed, all
he di e ences in he equency o sea ches we e signi ican and he di -
e ences conce ning he ypes o sou ces used we e ma ginally signi ican
(see able 1).
Table 1. Resou ce dominance di e ences be ween human ansla o s and pos -edi o s. Resul s o
he independen samples - es s
HUMAN
TRANSLATORS
(N = 10)
POST-EDITORS
(N = 12)
MSD MSD T-TEST P
Numbe o e mino-
lexicog aphic esou ces
2.70 3.08 1.16 1.36 1.74 .096
Numbe o ex -based
esou ces
1.90 0.99 0.92 1.24 2.02 .057
To al numbe o
esou ces used
4.60 1.65 2.75 2.38 2.08 .051
F equency o sea ches
(LEX)*
27.80 9.60 9.17 7.03 5.33 .000
F equency o sea ches
(TXT)*
8.50 5.87 2.50 3.99 2.81 .011
F equency o sea ches
( o al)*
36.30 8.41 11.75 9.93 6.18 .000
No e: * = signi ican di e ences
5.3. Numbe o co ec equi alen s o e ms ound
To answe esea ch ques ions 2 and 4, he success o inding he co ec a -
ge equi alen s had o be de e mined. Mean alues (HT = 1.40, PE = 1.67,
1s yea = 1.42, 2nd yea = 1.70) show ha s uden s we e no pa icula ly
151Te minologija | 2024 | 31
pa icipa ed in he da a collec ion. Fu he mo e, only one ex , a legal one
was used in he s udy and pa icipan s came om one ins i u ion. These
ac o s limi he gene alisabili y o he esul s, al hough signi ican ind-
ings may indica e alid endencies o se ings simila o ha o he s udy.
The lack o e bal da a om pa icipan s p e en ed he in e p e a ion o
ce ain indings, al hough i is clea ha one mus se limi s o he com-
plexi y o he esea ch design, oo.
The limi a ions o his s udy indica e he di ec ions o u u e esea ch.
The s udy could be epea ed wi h a la ge sample in ol ing p o essionals
and s uden s om o he uni e si ies o coun ies. A di e en ex ype
could be used and o he ypes o p ocess da a could be collec ed.
Mo eo e , he da a se o he p esen s udy has emained pa ly unex-
plo ed. Time spen on esea ch has no been measu ed o ela ed o indices
o esea ch beha iou o pe o mance. The use o ansla ion esou ces in
he di e en s ages o HT and PE (d a ing, e ision) could be s udied, oo,
jus like he numbe o e minology changes pos -edi o s make and hei
ela ion o esea ch s a egies.
Despi e i s limi a ions, he s udy ce ainly adds o ou unde s anding o
ansla ion ainees’ esou ce use. Ne e heless, mo e wo k needs o be done
in his ield o disco e wha esea ch s a egies and beha iou s a e needed
in he digi al e a whe e pos -edi ing will likely domina e ansla o s’ wo k.
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153Te minologija | 2024 | 31
APPENDIX 1.
The sou ce ex used o he s udy:
LICENCE TO PUBLISH
Manusc ip #: [name o jou nal] (“The Jou nal”)
Ti le o he con ibu ion: (“The Con ibu ion”)
Au ho (s): (“ he Au ho s”)
To: Na u e Publishing G oup (“NPG”), a di ision o Macmillan Publishe s L d
1. In conside a ion o NPG ag eeing o publish he Con ibu ion he Au ho s g an
o NPG o he ull e m o copy igh in he Con ibu ion and any ex ensions
he e o, subjec o clause 2 below, he exclusi e licence (a) o publish, ep oduce,
dis ibu e, display and s o e he Con ibu ion in all o ms, o ma s and media
whe he now known o he ea e de eloped (including wi hou limi a ion in p in ,
digi al and elec onic o m) h oughou he wo ld, (b) o ansla e he Con ibu i-
on in o o he languages, c ea e adap a ions, summa ies o ex ac s o he Con i-
bu ion o o he de i a i e wo ks based on he Con ibu ion and exe cise all o he
igh s ou lined in (a) abo e in such ansla ions, adap a ions, summa ies, ex ac s
and de i a i e wo ks and (c) o license o he s o do any o all o he abo e.
2. Owne ship o copy igh emains wi h he Au ho s and p o ided ha , when
ep oducing he Con ibu ion o ex ac s om i , he Au ho s acknowledge
i s and e e ence publica ion in he Jou nal, he Au ho s e ain he ollowing
nonexclusi e igh s:
a) To ep oduce he Con ibu ion in whole o in pa in any p in ed olume
(book o hesis) o which hey a e he au ho (s).
b) They and any academic ins i u ion whe e hey wo k a he ime may ep o-
duce he Con ibu ion o cou se eaching.
c) To pos a copy o he Con ibu ion as accep ed o publica ion a e pee
e iew (in Wo d o Tex o ma ) on he Au ho ’s own websi e o ins i u i-
onal eposi o y six mon hs a e publica ion o he p in ed edi ion o he
Jou nal, p o ided ha hey also gi e a hype link om he Con ibu ion o
he Jou nals web si e
d) To euse igu es o ables c ea ed by hem and con ained in he Con ibu-
ion o o he wo ks c ea ed by hem.
This Ag eemen shall be go e ned by and cons ued in acco dance wi h he laws
o England wi hou ega d o he p inciples o con lic s o law. The pa ies he e o
submi o he non-exclusi e ju isdic ion o he English cou s.
APPENDIX 2.
The 10 a ge e ms selec ed o he analysis:
licence o publish, con ibu ion, ull e m o copy igh , including wi hou limi-
a ion, o g an exclusi e licence, o ep oduce, de i a i e wo k, hesis, academic
ins i u ion, pee e iew
154 T ansla o s’ Resou ce Dominance and he Success o Finding
he Ta ge Te ms in Human T ansla ion and Pos -edi ing o
Machine T ansla ion
Esz e Se mann
Má a Lesznyák
VERTĖJŲ IŠTEKLIŲ DOMINAVIMAS IR SĖKMINGA VERTIMO KALBOS TERMINŲ PAIEŠKA
VERČIANT ŽMOGUI ARBA POSTREDAGUOJANT MAŠININĮ VERTIMĄ
San auka
Ve imo p iemonių naudojimas iš esmės pasikei ė pe pas a uosius du dešim mečius –
in e ne iniai skai meniniai iš ekliai be eik isiškai pakei ė popie ines p iemones. Šiuo-
laikinėje echnologinėje aplinkoje e ėjai gali naudo is daugybe in e ne inių skai -
meninių iš eklių, ačiau no in pasi ink i pa ikimas i eiksmingas p iemones, eikia
k uopš umo i disciplinos. Šiame y ime nag inėjamas e ėjų p ak ikan ų iš eklių
domina imas ą pa į eisinį eks ą e čian žmogui i pos edaguojan i analizuojami
galimi yšiai a p iš eklių domina imo, užduo ies a likimo laiko i sėkmingai as ų
eisingų e imo kalbos e minų.
Čia pa eik as y imas y a Segedo e imo kompe encijos y imų g upės bend ojo
y imo p ojek o, ku iuo siekiama iš i i e imo kompe encijos elemen ų (PACTE)
aidmenį žmogaus e ime i mašininio e imą pos edaga ime, dalis. Kadangi da-
ly aujame į p oduk ą o ien uo uose y imuose, daba p is a ome pi muosius e imo
p oceso y imo ezul a us.
Mūsų ezul a ai odo, kad e minog a iniai i leksikog a iniai šal iniai dominuoja
su e imu susijusiuose s uden ų y imuose. Be o, s uden ams ganė inai nesisekė as i
eisingų a i ikmenų e minams, jie ado idu iniškai ieną a du iš dešim ies. Be o, nei
laikas užduočiai, nei iš eklių domina imas nepa odė jokių eikšmingų ko eliacijų su
inkamų e imo kalbos e minų adimu. Ve ėjų i pos edak o ių palyginimas pa o-
dė, kad pos edak o iai di bo g eičiau i a liko mažiau paieškų nei e ėjai. Nepaisan
o, jų as ų e minų eisingumas bu o panašus į e ėjų.
Aki aizdu, kad y imas u i am ik ų ūkumų, iš ku ių ienas y a maža im is,
ačiau, nepaisan jų, iš ados ik ai p isideda p ie mūsų sup a imo apie e ėjų p ak i-
kan ų iš eklių naudojimą.
Gau a 2024-05-03
Esz e Se mann
Depa men o I alian Language and Li e a u e, Uni e si y o Szeged, Hunga y
6724 Szeged, Pulz u ca 1.
E-mail esz e .se [email protected]
Má a Lesznyák
Ins i u e o English and Ame ican S udies, Uni e si y o Szeged, Hunga y
6722 Szeged, Egye em u ca 2.
E mail [email protected]