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Terminology, translation, and PRESEMT; word frequency lists and KELLY

Adam Kilgarriff Lexical Computing Ltd. Terminology, translation, and PRESEMT; word frequency lists and KELLY. PRESEMT. EU FP7 project FP7-ICT-4-248307 2010-1012 P attern  Re cognition based  S tatistically  E nhanced  MT Six partners, five countries

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Terminology, translation, and PRESEMT; word frequency lists and KELLY

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  1. Adam Kilgarriff Lexical Computing Ltd Terminology, translation, and PRESEMT; word frequency lists and KELLY Kilgarriff: PRESEMT and KELLY

  2. PRESEMT • EU FP7 project • FP7-ICT-4-248307 • 2010-1012 • Pattern Recognition based Statistically Enhanced MT • Six partners, five countries • Languages: Czech English German Greek Italian • Comparable Corpora BootCat (CCBC) • Demo by Jan Pomikalek • http://www.presemt.eu Kilgarriff: PRESEMT and KELLY

  3. KELLY • “Keywords for Language Learning for Young and adults alike” • EU lifelong learning project: • Goal: wordcards • Word in one lg on one side, other on other • Language learning • 9 languages, 36 pairs • Arabic Chinese English Greek Italian Norwegian Polish Russian Sweden • Partners in 6 countries • http://su.avedas.com/converis/contract/321 Kilgarriff: PRESEMT and KELLY

  4. Kilgarriff: PRESEMT and KELLY

  5. Method • Prepare monolingual lists • Translate • Each into 8 target languages • Professional translation services • Integrate, finalise • Produce cards • Goal for each set • 9000 pairs at 6 levels Kilgarriff: PRESEMT and KELLY

  6. Stages • Sort out corpora, tagging • Automatically generate M1 lists • names, numbers, countries ... • keywords vis-a-vis other corpora • Review, compare, prepare M2 lists • Translate • Use translations: M3 lists • Finalise Kilgarriff: PRESEMT and KELLY

  7. review - how? • points system • 2 points for each of 6 levels • 12 points for most freq words • deduct points for words in over-represented areas • add in words from other corpora Kilgarriff: PRESEMT and KELLY

  8. Translation database • On the web • All translations entered into it • Queries like • All Swedish words used as translations more than six times • All 1:1:1:1... 'simple cases' Kilgarriff: PRESEMT and KELLY

  9. Using the translations database • Find words not in M2 lists, that need adding • Multiwords • English look for • Probably, the translation of a high-freq word in several of the 8 other lgs • So: • add it to English list • Homonyms: could be similar Kilgarriff: PRESEMT and KELLY

  10. Monolingual master lists (M3)‏ • Based on a WAC corpus • Input from other same-lg corpora • And from translations from 8 lgs • Useful words which might not be hi-freq • added words/multiwords must be above a lower freq threshold • Target 9000 Kilgarriff: PRESEMT and KELLY

  11. Matches across 9 languages • Set of symmetrical relations across all 36 pairs • music • library • sun • hospital • theory Kilgarriff: PRESEMT and KELLY

  12. Big problems • Multiwords (as anticipated)‏ • Homonymy (as anticipated)‏ • orange banana alphabet elbow, Hello • Worse than anticipated • Lists from spoken corpora, learner corpora, needed • Relation between • Competence for communicating • The corpora at our disposal Kilgarriff: PRESEMT and KELLY

  13. Kilgarriff: PRESEMT and KELLY (Monolingual) Word Lists Define a syllabus Which words get used in Learning-to-read books (NS children)‏ NNS language learner textbooks Dictionaries Language testing NS: educational psychologists NNS: proficiency levels

  14. Kilgarriff: PRESEMT and KELLY Should be corpus-based Most aren't Corpora are quite new Easy to do better People will use them Maybe also Governments

  15. Kilgarriff: PRESEMT and KELLY How Take your corpus Count Voila

  16. Kilgarriff: PRESEMT and KELLY Complications What is a word Words and lemmas Grammatical classes Numbers, names... Multiwords Homonymy All are slightly different issues for each lg

  17. Kilgarriff: PRESEMT and KELLY What is a word; delimiters Found between spaces Not for Chinese: segmentation English co-operate, widely-held, farmer's, can't Norwegian, Swedish Compounding, separable verbs Arabic, Italian Clitics, al, ... ...

  18. Kilgarriff: PRESEMT and KELLY Words and lemmas Word form (in text)‏ invading Lemma (dictionary headword)‏ Invade for forms invade invades invaded invading Lemmatisation Chinese, none; English, simple Middling: Swe Nor It Gr Tough: Rus, Pol, Ara

  19. Kilgarriff: PRESEMT and KELLY Word Families • Derivational morphology • efficient/efficiently • access/accessible/accessibility • available/availability/unavailable • ‘Word families’ tradition • eg: Coxhead, Academic word list • Pedagogy: one item to learn • But • Where do families end? Different meanings

  20. Kilgarriff: PRESEMT and KELLY Grammatical classes brush (verb) and brush (noun)‏ Same item or different? (both in same word family) Required (short) list of word classes POS-tagger Will make mistakes

  21. Kilgarriff: PRESEMT and KELLY Marginal cases Numbers twelve, seventeenth, fifties Closed sets Days of week, months Countries Capitals, nationalities, currencies, adjectives, languages regional/dialects, political groups, religions easter, christmas, islam, republican policies always needed

  22. Kilgarriff: PRESEMT and KELLY Multiwords According to Linguistically a word but Multiword frequency list: top item of the Can't use freqs (alone) to select multiwords

  23. Kilgarriff: PRESEMT and KELLY Homonymy bank (river) and bank (money)‏ Word sense disambiguation We can't do (with decent accuracy)‏ We can't give freqs for senses Lists of words not meanings Sometimes disconcerting

  24. Kilgarriff: PRESEMT and KELLY Corpora A fairly arbitrary sample of a lg To limit arbitrariness of wordlist Make it big and diverse WACKY corpora From web Can do for any language ??? Comparable ??? Web language: less formal

  25. Kilgarriff: PRESEMT and KELLY Word lists are useful, but ...are they scientific? A tiny bit, occasionally ...could they be scientific? Yes article of faith By the end of KELLY, we'll have a clearer idea how

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