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HASK | COLLOCATION  DATABASES
Citation Please cite this paper in publications using HASK for the BNC: Pezik, Piotr. Graph-Based Analysis of Collocational Profiles. In Phraseologie Im Wörterbuch Und Korpus (Phraseology in Dictionaries and Corpora), edited by Vida Jesenšek and Peter Grzybek, 227–43. ZORA 97. Maribor, Bielsko‑Biała, Budapest, Kansas, Praha: Filozofska fakuteta, 2014.
150,045entries containing2,875,407combinations...
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excelSpreadsheet
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# Collocate POS A TTEST MI3 CHISQ JD R AWT fAWT Details Equivalents
1. kill kill
killed
Killing
kills
Verb 30 5.18 14.03 499.42 0.58 12 8,086,859 6.72
2. save save
saved
saving
Verb 19 4.07 12.42 252.42 0.75 16 4,501,033 12.08
3. minke minke Verb 9 3 18.85 52,574.78 0.4 5 12,153,801 4.47
4. catch catch
catches
catching
caught
Verb 11 2.85 9.76 58.52 0.41 5 12,296,607 4.42
5. seal seal
sealing
seals
Verb 7 2.59 11.12 304.11 0.49 5 13,538,108 4.02
6. resume resume Verb 6 2.37 10.11 172.79 0.15 2 49,201,724 1.1
7. include include
included
Verb 6 0.88 5.81 1.2 0.43 4 14,872,269 3.66
8. believe believe
believed
Verb 5 0.58 5.08 0.46 0.56 5 14,324,275 3.79
9. turn turned
turns
Verb 5 0.08 4.7 0.01 0.34 3 25,615,771 2.12
10. use use
used
uses
Using
Verb 8 -1.88 5.26 2.15 0.54 6 14,146,500 3.84
11. see saw
see
seen
sees
Verb 13 -2.04 6.75 2.7 0.59 8 8,696,458 6.25
12. may may Verb 6 -2.62 4.12 3.34 0.53 5 21,070,501 2.58
13. make made
make
makes
making
Verb 12 -3.19 6.23 5.4 0.64 9 9,953,747 5.46
14. could could Verb 7 -4.01 4.28 6.49 0.53 5 25,411,054 2.14
15. will will
wo
Verb 13 -4.32 6.27 8.66 0.61 8 10,565,609 5.14
16. take take
taken
takes
taking
took
Verb 6 -5.35 3.5 9.11 0.53 5 16,867,124 3.22
17. have 've
had
has
have
having
Verb 82 -6.41 11.94 26.83 0.77 38 2,088,915 26.02
18. can ca
can
Verb 9 -6.61 4.66 13.94 0.5 6 16,552,456 3.28
19. would would Verb 10 -7.01 4.96 15.65 0.66 9 9,884,610 5.5
20. go go
goes
going
Verb 5 -8.89 2.33 16.19 0.56 5 40,346,956 1.35
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