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ETAP-3: State of the Art, Options, and Prospects of Development

ETAP-3: State of the Art, Options, and Prospects of Development. Leonid Iomdin Institute for Information Transmission Problems Russian Academy of Sciences iomdin @iitp.ru. Theoretical Background. I gor Mel’ č uk: «Meaning  Text» theory J u rij Apresjan:

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ETAP-3: State of the Art, Options, and Prospects of Development

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  1. ETAP-3: State of the Art, Options, and Prospects of Development Leonid Iomdin Institute for Information Transmission Problems Russian Academy of Sciences iomdin@iitp.ru

  2. Theoretical Background • Igor Mel’čuk: «Meaning  Text» theory • Jurij Apresjan: Integrated Theory of Linguistic Description and Systemiclexicography Prague, May 12, 2008

  3. ETAP-3Options • Machine translation • SynTagRus: the tagged corpus of Russian Texts • Generation from and to UNL • (Quasi)synonymous Paraphrasing • Computer-Aided Language Learning Tool Prague, May 12, 2008

  4. Machine Translation • Russian  English • 120,000-strong morphological dictionaries • 95,000-strong combinatorial dictionaries • Russian  German prototype • Russian  French prototype • Russian  Korean prototype • Russian  Spanish prototype • Arabic  English prototype Prague, May 12, 2008

  5. Major Features of ETAP Environment • Rule-based Approach • Stratificational Approach • Syntactic Dependencies • Lexicalistic Approach • Self-Tuning • Maximum Reusability of Linguistic resources Prague, May 12, 2008

  6. General Layout of Translation Process Prague, May 12, 2008

  7. Dependency Syntactic Structure • They made a general remark that it was true. Prague, May 12, 2008

  8. Self-Tuning: Grammar vs. Dictionary • General regularities: general rules that apply to very large classes of words and occur very often. • Example: agreement Adj + N • Restricted-scope regularities: specific rules that apply to restricted classes of words and have limited occurrence. • Example: compound numerals Prague, May 12, 2008

  9. Multiple Translation They made a general remark that … • (a) ‘they remarked in a general way that…’ • (b) ‘they forced a general to remark that…’ Prague, May 12, 2008

  10. Synonymous Paraphrasing • The director ordered John to write a report • The director gave John an order to write a report • John was ordered by the director to write a report • John received an order from the director to write a report Prague, May 12, 2008

  11. Lexical Functions • Substitute LF • synonyms, antonyms, converse terms, derivatives • Collocate LF • MAGN = 'a high degree of what is denoted by X’ • OPER/FUNC • ... Prague, May 12, 2008

  12. Lexical Functions • MAGN disease grave • MAGN fog heavy • MAGN control strict Prague, May 12, 2008

  13. Oper / Func Family of LF Prague, May 12, 2008

  14. Examples of LF Oper • Oper1 (invitation) = issue • Oper2(invitation) = receive • Oper1 (defeat) = suffer • Oper2 (resistence) = encounter • Oper2 (respect) = enjoy Prague, May 12, 2008

  15. Examples of LF Func • Func1 (fear) = possess • Func2 (decision) = concern • Func1 (responsibility) = rest (with) • Func2 (vengeance) = fall (upon) Prague, May 12, 2008

  16. General Properties of Lexical Functions • Universality • Intralinguistic idiomaticity • grave disease, heavy fog • *heavy disease, *grave fog. • Cross-linguistic idiomaticity • Rus. тяжелая болезнь‘heavy disease’ • Rus. густой туман‘dense fog’ Prague, May 12, 2008

  17. General Properties of Lexical Functions (cont.) • Paraphrasing Potential: • He respects [X] his teachers • He has [OPER1 (S0 (X))] respect [S0 (X)] for his teachers • He treats [LABOR12 (S0 (X))] his teachers with respect • His teachersenjoy [OPER2 (S0(X))] his respect Prague, May 12, 2008

  18. LF in Practical Applications • Syntactic and Lexical Ambiguity Resolution in Parsers • Idiomatic Translation of a Large Class of Set Expressions in Machine Translation • Sentence Paraphrasing Prague, May 12, 2008

  19. Lexical Ambiguity Resolution • to draw a distinction - provodit' razlichie • Both verbs are extremely ambiguous: • draw - more than 50 meanings • provodit’ - more than 10 meanings Prague, May 12, 2008

  20. Syntactic Ambiguity Resolution • support of the parliament • 'support by the parliament' • 'support (given) to the parliament' • The president had [Y=OPER2(X)]the support [X] of the parliament • The fear [X] of his wife possessed [Y = FUNC1 (X)] Peter • The fears of his wife infectedPeter. Prague, May 12, 2008

  21. Idiomatic translation: LF Temp • March: in - март: в2 • Tuesday: on - вторник: в1 • dawn: at - рассвет: на2 • moment: at - момент: в1 • Easter: at – пасха: на1 Prague, May 12, 2008

  22. Sentence Paraphrasing • X = CONV12 (X) This group consists of 20 persons – Twenty persons comprise this group; • X + Y = ANTI1(X) + ANTI2(Y) He began to observe the rules – He stopped violating the rules • X = LABOR12 + S0(X) He respects his parents – He treats his parents with respect Prague, May 12, 2008

  23. Sample Dictionary Entry (Excerpt): CHANCE CHANCE1 POR:S SYNT:COUNT,PREDTO,PREDTHAT DES:'FACT','ABSTRACT’ Prague, May 12, 2008

  24. CHANCE D1.1:OF,'PERSON' D2.1:OF,'FACT' D2.2:TO2 D2.3:THAT1 Prague, May 12, 2008

  25. CHANCE SYN1: OPPORTUNITY MAGN: GOOD1, FAIR1, EXCELLENT ANTIMAGN: SLIGHT, SLIM, POOR, LITTLE1, SMALL OPER1: HAVE, STAND1 REAL1-M: TAKE Prague, May 12, 2008

  26. CHANCE ANTIREAL1-M: MISS1 INCEPOPER1: GET FINOPER1: LOSE CAUSFUNC1: GIVE <TO1> ZONE:R TRANS:ШАНС/СЛУЧАЙ Prague, May 12, 2008

  27. CHANCE REG:TRADUCT2.00 TAKE:X LOC:R R:COMPOS/MODIF/POSSES CHECK 1.1 DEP-LEXA(X,Z,PREPOS,BY1) N:01 CHECK 1.1 DOM(X,*,R) DO 1 ZAMRUZ:Z(PO1) 2 ZAMRUZ:X(SLUCHAJNOST’) Prague, May 12, 2008

  28. CHANCE • N:02 • CHECK • 2.1 DOM(X,*,*) • DO • 1 ZAMRUZ:Z(SLUCHAJNO) • 2 STERUZ:X • TRAF:RA-EXPANS.16 • LA:THAT1 • TRAF:RA-EXPANS.22 Prague, May 12, 2008

  29. What is UNL? • UNL is a formal language for meaning representation • A minimal unit of UNL is a UNL expression • UNL expression corresponds to a sentence of natural language in the amount of information conveyed Prague, May 12, 2008

  30. UNL System Chinese People French Chinese French People Spanish Hindi Internet Hindu People Spanish People UNL Architecture Prague, May 12, 2008

  31. How is UNL made? • UNL is a formal language of meaning representation • A minimum UNL unit is UNL graph • The amount of sense rendered by a UNL graph corresponds to a natural language sentence Prague, May 12, 2008

  32. Two MT architectures: Transfer vs. Interlingua Source text Target text Transfer Interlingua Prague, May 12, 2008

  33. UNL approach to lexical design Semantic units of UNL (universal words, UW) are designed on the basis of natural language (English) words which can be semantically modified if need be Prague, May 12, 2008

  34. UNL strategy Lexical meanings of the natural language are represented by UWs. • Lexical meaning coincides with the meaning of an unambiguous English word • Lexical meaning coincides with one of the senses of an unambiguous English word • Lexical meaning does not coincide with any of the lexical meanings of English Prague, May 12, 2008

  35. Disambiguation of natural word senses Coach: bus, trainer, train, drill,... • coach(icl>bus>transport) • сoach(icl>person,obj>sportsman) • coach(icl>do,obj>sportsman) • coach(icl>do,obj>student) Prague, May 12, 2008

  36. Formation of new UWs прибежать прилететь приплыть приползти come(met>run) come(met>plane) come(met>swim) come(met>crawl) Prague, May 12, 2008

  37. Formation of new UWs жениться marry(agt>man) выходить замуж marry(agt>woman) Prague, May 12, 2008

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