The document discusses DUCKS (Data Unified Concept Knowledge Sets), a tool that aims to build a broad multilingual lexicon by aligning open linguistic data through crowdsourcing. DUCKS allows users to match terms from different languages to concepts, with the goal of creating a complete matrix of human expression across languages over time. Currently, DUCKS contains over 100,000 English concepts from Princeton WordNet aligned to about 60 other languages via Global WordNet. The document provides examples of how specific languages like Fula and Kemedzung have been added to DUCKS from digital lexicons.

1. Martin Benjamin, Sina Mansour, Karl Aberer
DUCKS in a Row:
Aligning open linguistic data through crowdsourcing to build a broad multilingual lexicon
Vital Voices: Linking Language and Wellbeing
5th International Conference on Language Documentation and Conservation
Honolulu, Hawaii - March 5, 2017 1

2. 2
1. Multilingual lexicography:
problems and principles
2. DUCKS: Data Unified Concept
Knowledge Sets
a. The tool
b. The data
3. Your language in DUCKS

3. kamusi is Swahili for dictionary
3

4. Goal: A complete matrix of human expression across time and space
• As a knowledge resource
• As a data resource
4

5. In service since 1994 (originally at Yale Council on African Studies)
International NGO since 2009
• Registered non-profit in USA and Switzerland
Academic Home since 2013:
EPFL - Swiss Federal Institute of Technology in Lausanne
LSIR - Distributed Systems Information Laboratory 5

6. White House Big Data Initiative:
Launch Partner for Building the Data Innovation Ecosystem
Networking and Information Technology R&D Program
Office of Science and Technology Policy 6

7. 7
1. Multilingual lexicography:
problems and principles
2. DUCKS: Data Unified Concept
Knowledge Sets
a. The tool
b. The data
3. Your language in DUCKS

8. light
8

9. light
why multilingual dictionaries were impossible
9

10. light
lumineux
léger
allégé
léger
why multilingual dictionaries were impossible
10

11. light
lumineux
léger
allégé
léger
why multilingual dictionaries were impossible
WOLF 02121424-a:
léger
lumière
WOLF 01186408-a:
léger
WOLF 00993117-a:
léger
allégé
lumière
light
WOLF 00269989-a:
lumière
lumineux
clair
PWN (English Wordnet):
light x 47
WOLF (French Wordnet):
light = lumière x 44
light = léger x 37
léger = lumière x 36
11

12. light
léger
why multilingual dictionaries were impossible
lumineux
allégé
léger
12

13. why multilingual dictionaries were impossible
13

14. why multilingual dictionaries were impossible
lumineux
14

15. 15

16. light
fr: lumineux
fr: léger
fr: allégé
fr: léger
why multilingual dictionaries were impossible
th: ที่แคลอรี่ต่ำ
fi: kaloriton
sw: pungufu
th: เบำ
fi: kevyt
sw: -epesi
th: สว่ำง
fi: valoisasw: -enye mwanga
th: ซึ่งไร้สำระ
fi: tyhjänpäiväinen
sw: -a kuchekesha
16

17. en: light
fr: lumineux
fr: léger
fr: allégé
fr: léger
why multilingual dictionaries were impossible
th: ที่แคลอรี่ต่ำ
fi: kaloriton
sw: pungufu
th: เบำ
fi: kevyt
sw: -epesi
th: สว่ำง
fi: valoisasw: -enye mwanga
th: ซึ่งไร้สำระ
fi: tyhjänpäiväinen
sw: -a kuchekesha
en: light
en: light
en: light
17

18. fr: lumineux
fr: léger
fr: allégé
why multilingual dictionaries were impossible
th: ที่แคลอรี่ต่ำ
fi: kaloriton
sw: pungufu
th: เบำ
fi: kevyt
sw: -epesi
th: สว่ำง
fi: valoisasw: -enye mwanga
light
fr: léger
th: ซึ่งไร้สำระ
fi: tyhjänpäiväinen
sw: -a kuchekesha
18

19. why multilingual dictionaries were impossible
19

20. light
how Kamusi makes a multilingual dictionary possible
20

21. light (not serious)
light (not fattening)
light (not heavy)
light (not dark)
how Kamusi makes a multilingual dictionary possible
21

22. light (not serious)
light (not fattening)
light (not heavy)
light (not dark)
how Kamusi makes a multilingual dictionary possible
fr: lumineux
fr: léger
fr: allégé
fr: léger
22

23. light (not serious)
light (not fattening)
light (not heavy)
light (not dark)
how Kamusi makes a multilingual dictionary possible
fr: lumineux th: สว่ำงfi: valoisasw: -enye mwanga
23

24. light (not serious)
light (not fattening)
light (not heavy)
light (not dark)
how Kamusi makes a multilingual dictionary possible
fr: léger th: เบำfi: kevytsw: -epesi
24

25. light (not serious)
light (not fattening)
light (not heavy)
light (not dark)
how Kamusi makes a multilingual dictionary possible
fr: léger th: ซึ่งไร้สำระfi: tyhjänpäiväinensw: -a kuchekesha
25

26. light (not serious)
light (not fattening)
light (not heavy)
light (not dark)
how Kamusi makes a multilingual dictionary possible
fr: allégé th: ที่แคลอรี่ต่ำfi: kaloritonsw: pungufu
26

27. light (not serious)
light (not fattening)
light (not heavy)
light (not dark)
how Kamusi makes a multilingual dictionary possible
fr: allégé th: ที่แคลอรี่ต่ำfi: kaloritonsw: pungufu
fr: léger th: ซึ่งไร้สำระfi: hölynpölysw: -a kuchekesha
fr: léger th: เบำfi: kevytsw: -epesi
fr: lumineux th: สว่ำงfi: valoisasw: -enye mwanga
27

28. how Kamusi makes a multilingual dictionary possible
light (not heavy) fr: léger th: เบำfi: kevytsw: -epesi
fr: léger (sandy)
fr: léger (low alcohol)
fr: léger (without much luggage)
28

29. light (not serious)
light (not fattening)
light (not heavy)
light (not dark)
how Kamusi makes a multilingual dictionary possible
29

30. light (not serious)
light (not fattening)
light (not heavy)
light (not dark)
how Kamusi makes a multilingual dictionary possible
30

31. light (not serious)
light (not fattening)
light (not heavy)
light (not dark)
how Kamusi makes a multilingual dictionary possible
31

32. light (not serious)
light (not fattening)
light (not heavy)
light (not dark)
how Kamusi makes a multilingual dictionary possible
32

33. light (not serious)
light (not fattening)
light (not heavy)
light (not dark)
how Kamusi makes a multilingual dictionary possible
33

34. light (not serious)
light (not fattening)
light (not heavy)
light (not dark)
how Kamusi makes a multilingual dictionary possible
34

35. 35

36. Side by Side Vocabulary Translation:
KamusiGOLD vs. Google Translate
36

37. equivalence
• Parallel
• Similar
• Explanatory
translations 37

38. equivalence
• Parallel
• Similar
• Explanatory
hand (English) = main (French)
✓: transitive across languages
translations 38

39. equivalence
• Parallel
• Similar
• Explanatory
mkono (Swahili) = hand + arm (English)
⁇ : might be transitive across languages
mkono (Swahili) = lima (Hawaiian)
translations
difference difference translation
39

40. equivalence
• Parallel
• Similar
• Explanatory (Lexical Gaps)
hand (English) = 10.2 cm (most languages)
✗: not transitive across languages
translations 40

41. 41
1. Multilingual lexicography:
problems and principles
2. DUCKS: Data Unified Concept
Knowledge Sets
a. The tool
b. The data
3. Your language in DUCKS

42. • over 100,000 English defined concepts from Princeton Wordnet
• Heavy Anglo-American bias
• James Cook yes, Kalaniʻōpuʻu-a-Kaiamamao no
• about 60 languages aligned via Global Wordnet
• over 800,000 English concepts from Wiktionary (in process)
• Wiktionary translations to many languages (highly problematic)
• other languages (Spanish already) can be pivots when:
• aligned to DUCKS
• entries have definitions
42

43. • Players match term from the left with
concept on the right
• Multiple matches possible
• Bad definitions can be flagged
• Null matches: on indigenous concepts:
43

44. Still to come:
•Multiplayer – validation by consensus
•Manual term searching
•DUCKS for FLEx
44

45. 45
1. Multilingual lexicography:
problems and principles
2. DUCKS: Data Unified Concept
Knowledge Sets
a. The tool
b. The data
3. Your language in DUCKS

46. Switch flippable:
• About 60 wordlists and datasets data prepared and
permissions granted
• SignTyp set for ~20 sign languages
• Comparative African Wordlist – pre-aligned, no need for
the tool
• Any lexicon in a useable digital format that is copyright
available
46

47. What we can work with:
• Word lists
• part of speech is helpful
• Electronic versions of print dictionaries
• parse and play
• Digital dictionaries
• FLEx, etc
47

48. 48
Kemedzung (Cameroon) from FLEx

49. 49
Fula (West Africa)
ABADA Ar
abada, abadaa, abadan DFZ Z<->
never(F) (with negation); ever(F); long ago
jamais(D) (avec la négation)(Z); jamais; il y a longtemps
Abada mi yahaali. (F): I have never gone. ; Je ne suis jamais allé.
abada pati (F): don't ever ; ne faîtes jamais (qqch)
gila abada (F): since long ago, forever ; depuis longtemps, toujours
11,000 Fula senses
• 332 clearly computable matches
• ~7500 matches for DUCKS
• ~3000 null matches for manual follow-up

50. 50

51. 51
1. Multilingual lexicography:
problems and principles
2. DUCKS: Data Unified Concept
Knowledge Sets
a. The tool
b. The data
3. Your language in DUCKS

52. 52
1. Multilingual lexicography:
problems and principles
2. DUCKS: Data Unified Concept
Knowledge Sets
a. The tool
b. The data
3. Your language in DUCKS

53. 53
1. Multilingual lexicography:
problems and principles
2. DUCKS: Data Unified Concept
Knowledge Sets
a. The tool
b. The data
3. Your language in DUCKS

54. 54
1. Multilingual lexicography:
problems and principles
2. DUCKS: Data Unified Concept
Knowledge Sets
a. The tool
b. The data
3. Your language in DUCKS

55. 55
1. Multilingual lexicography:
problems and principles
2. DUCKS: Data Unified Concept
Knowledge Sets
a. The tool
b. The data
3. Your language in DUCKS

56. 56
1. Multilingual lexicography:
problems and principles
2. DUCKS: Data Unified Concept
Knowledge Sets
a. The tool
b. The data
3. Your language in DUCKS

57. Martin Benjamin, Sina Mansour, Karl Aberer
DUCKS in a Row:
Aligning open linguistic data through crowdsourcing to build a broad multilingual lexicon
Vital Voices: Linking Language and Wellbeing
5th International Conference on Language Documentation and Conservation
Honolulu, Hawaii - March 5, 2017 57