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Automatic translation quality control using Eurovoc descriptors Marko Tadić, Božo Bekavac

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1 Automatic translation quality control using Eurovoc descriptors Marko Tadić, Božo Bekavac (marko.tadic@ffzg.hr, http://www.hnk.ffzg.hr/mt/ bbekavac@ffzg.hr, http://www.hnk.ffzg.hr/bb/) Department of linguistics / Institute of linguistics, Faculty of Philosophy, University of Zagreb (www.ffzg.hr, www.hnk.ffzg.hr) JRC Ispra / Arona, 2005-09-27

2 Talk plan motivation automatic translation quality control resources: glossary and test corpus results further directions

3 Motivation Acquis communautaire (AC) is still being translated to Croatian former Ministry of European Integrations (MEI), today Ministry of External Affairs and European Integrations AC –ca 200,000 pages of EU OJ –AC corpus: from 8 Mw (Estonian) to 82 Mw (Spanish) –not precisely delimited (lawyers are working on that!) –constantly growing –legal texts a lot of repetitious and formulaic expressions low polysemy in terms expected

4 Motivation 2 different EU accession candidates  different organization of translation process –several years of work –large number of translators –in-house/out-house (tenders) –large-scale document translation and revision MEI –outsourcing to ca 100 translators or translating companies –use of glossary with pre-established TEs –glossaries being translated in advance Eurovoc EU Law Glossary / Čtyřjazyčný slovník práva Evropské unie, Prague 1999 maintain the consistency of translation –by use of the same glossary only?

5 Preparing AC originals for translation project proposed by our Institute to MEI in 2002 entries from glossary marked in original text before translation signal of the existence of pre-established TE to the translator obligatory usage of existing TE in legal texts, e.g.: –Council of EuropeVijeće Europe –European CouncilEuropsko vijeće –Council of the European UnionVijeće Europske unije... AC had to be converted to XML MEI dropped the project in 2003 for the lack of finances now: AC corpus in XML

6 Revision of Translation largest effort was put on translation in all candidate countries revision of translation always in the last place –quality: consistency task undermined by all candidate countries –large portions of official translation of AC poorly revised usually done –manually –simple search & replace commands –no terms/entries marked in texts automatic approach? –lexical level and idiomatic level

7 Automatic Translation Quality Control use system to check whether all pre-established TE are used –sentence aligned parallel corpus –glossary entries marked in original text translated text if a TE of a glossary entry found in original, has not been found in aligned translated sentence  translation is departing from pre-established TE e.g.: –Eurovoc:(en) President of the Commission = (hr) Predsjednik Komisije –Corpus:(en) … if the President of the Commission declares … (hr 1 ) … ako Predsjednik Komisije objavi … (hr 2 ) … ako Predsjednik objavi …

8 Resources our lexicon: Eurovoc 4.1 –documentational indexing glossary –ca 6000 entries (descriptors) covering topics found in EU legal texts –accompanied by non-descriptors (synonyms) –translated to Croatian in 2000 –+ 4000 Croatian specific descriptors –translation always 1:1 –combination of nouns, adjectives, prepositions, conjunctions our corpus: 9 documents from AC corpus and their translations from MEI –size:16.053 tokens (en) 13.590 tokens (hr) –Croatian translations converted to AC corpus XML format

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10 Method simple glossary look-up? problem of inflection –English at least: sg, pl, ’s –Croatian 7 cases  2 numbers for nouns 7 cases  2 numbers  3 genders  2 definiteness  3 comparison for Adjectives lemmatization of corpus or glossary? Eurovoc lemmatized and converted to FSA: Intex –English lemmatizer from Intex for English Eurovoc –Croatian Lemmatization Server (hml.ffzg.hr) for Croatian Eurovoc –FSA with 10430 states

11 Eurovoc as FSA " / " 320 300 1 2

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13 Method 2 glossary entires marked in corpus together with IDs – checking whether the same ID appears on both sides of alignment (Perl script)          statistics en hr 652 656 13281484 with matched IDs 803 (60,47%) matched s are also word/phrase aligned parts below

14 Drawbacks syntactic merging –abbreviations not matched / marked (e.g. EP delegation vs. European Parliament delegation) –merged terms not matched / marked (e.g. head of State, head of government vs. heads of State or Government) EUROVOC = glossary intended for indexing –a lot of real terms (MWU) not matched / marked (e.g. country candidate to EU accession, Stabilisation and Association Agreement)  they don’t exist as entries –no semantic processing  polysemous terms wrongly matched / marked (e.g....which might lead (olovo) to a common defence...) Intex English lemmatizer didn’t cover all Eurovoc entries

15 Further directions evaluation of matched pairs of regarding –single-word units –multi-word units improving Intex English lemmatizer / lexicon use Eurovoc non-descriptors as synonyms –to capture a wider departure from expected TE in translation more precisely use / include other glossaries –EU Law Glossary test the whole system on larger corpus use it with other languages

16 Automatic translation quality control using Eurovoc descriptors Marko Tadić, Božo Bekavac (marko.tadic@ffzg.hr, http://www.hnk.ffzg.hr/mt/ bbekavac@ffzg.hr, http://www.hnk.ffzg.hr/bb/) Department of linguistics / Institute of linguistics, Faculty of Philosophy, University of Zagreb (www.ffzg.hr, www.hnk.ffzg.hr) JRC Ispra / Arona, 2005-09-27


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