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Poster: Method for an automatic generation of a semantic-level contextual translational dictionary
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Poster: Method for an automatic generation of a semantic-level contextual translational dictionary


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  • 1. METHOD FOR AN AUTOMATIC GENERATION OF A SEMANTIC-LEVEL CONTEXTUAL TRANSLATIONAL DICTIONARY Dmitry Kan Faculty of Applied Mathematics and Control Processes, St. Petersburg State Department of Technology of Programming, University Peterhof, Russia Abstract Word alignment Translational dictionaryIn this paper we demonstrate the semanticfeature machine translation (MT) systemas a combination of two fundamentalapproaches, where the rule-based side is Desperate to hold onto power , Pervezsupported by the functional model of the Musharraf hasRussian language and the statistical side discarded Pakistan s constitutional framework andutilizes statistical word alignment. The declared a state of emergency .MT system relies on a semantic-level NULL ({20}) В ({}) отчаянном ({1 3 4})contextual translational dictionary as its стремлении ({2}) удержать ({}) властьkey component. We will present the ({5}) ,method for an automatic generation of the ({6}) Первез ({7}) Мушарраф ({8}) от- Parallel corpus: UMC 0.1 верг ({9 10}) 86000 pairs of sentencesdictionary where disambiguation is done конституционную ({14 15}) 1,3 million phrase pairson a semantic level. систему ({}) Пакистана ({11 12 13}) и ({16}) ~18000 resulting dictionary entries объявил ({17}) о ({18}) введении ({}) В Y1>HabU(Y1:,ПРЕД:Z1) чрезвычайного ({19 21}) <149>--->Within Computer semantics theory положения ({}) . ({22}) В Y1>Loc(Y1:,ВНУТРИ$12/313/05Thesis 1. Language is an algebraic system Table 1: Word alignment for English and Russian sentences (ПРЕД:Z1)) <146>--->at{f1, .., fn, M}, where fi is basis function and Russian English В Y1>Loc(Y1:,Oper01(#,ПРЕД:Z1))M is data structure (set of basis concepts) of NULL of <208>--->Ina natural language L. В Y1>Loc(Y1:,ПРЕД:Z1) отчаянном Desperate to holdThesis 2. Each word in a sentence S is the <224>--->Throughout стремлении to of its semantic function. власть power НА Y1>Direkt(Y1:,ВЕРХ$12/141/05 (ВИН:Z1)) S  F ( f1 ( w11 ,..., w1k ),..., f n ( wn1 ,..., wnl )), , , <67>--->at Первез Pervez НА Y1>Direkt(Y1:,РОД:Z1) <100>- wij  whm , i  h, j  m -->on Мушарраф MusharrafThesis 3. Grammar links with semantics and отверг has discarded НА Y1>Direkt(Y1:,РОД:Z1) <69>--can be incorporated into semantics ->for конституционную constitutional framework ...dictionary ОБРАЗ (РОД:Z1) <2>--->a way Пакистана Pakistan ´ s ОБЩЕМИРОВОЙ A1>RelSemantic Machine Translation и and (A1:НЕЧТО$1,ПОЛНЫЙ$12/207/05 (МИР$1227)) Model объявил declared <1>--->global о a ...SMTM P  чрезвычайного state emergencyarg max  (t ,..., t )  arg max  i (tk , tl ) S s . . i 1,n i 1 m k 1,m 1 i l 2 ,mwhere 1, t k tl  L M  i (t , t )   S 2 k l 0, t k tl  L M 2 Features of Machine Translation System  dictionary entries contain semantic attributes of the Russian words  the MT system is automatically extendable through acquiring new par-  each entry represents a sample of a context extracted using statistical allel corpora and applying the method of word alignment with semantic word alignment and coded with the corresponding semantic formula; analysis of sentences on source language side