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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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# Collocate POS A TTEST MI3 CHISQ JD R AWT fAWT Details Equivalents
1. do did
do
does 		Verb 7 -48.48 1.34 127.15 0.58 6 13,937,372 3.9
2. be 're
are
be
been
being
is
was
were 		Verb 361 -35.81 15.46 665.99 0.83 79 733,909 74.07
3. have 've
had
has
have 		Verb 90 -24.52 11.14 187.06 0.84 46 1,732,844 31.37
4. see saw
see 		Verb 7 -15.08 2.87 34.47 0.58 6 18,525,697 2.93
5. would would Verb 18 -13.22 6.3 43.52 0.74 15 4,463,812 12.18
6. get get
getting
got 		Verb 12 -12.13 5 33.25 0.68 10 10,689,329 5.09
7. take take
taken
took 		Verb 10 -10.75 4.51 26.65 0.64 8 14,910,831 3.65
8. make made
make
makes
making 		Verb 14 -10.46 5.69 29.33 0.71 12 17,740,453 3.06
9. give give
given
giving 		Verb 7 -9.34 3.43 19.47 0.53 5 42,208,246 1.29
10. come came
come
comes
coming 		Verb 9 -9.22 4.31 21.13 0.64 8 12,279,864 4.43
11. should should Verb 7 -7.81 3.63 15.58 0.49 5 13,598,831 4
12. find find
found 		Verb 6 -7.46 3.15 13.88 0.6 6 15,681,360 3.47
13. will will Verb 28 -7.14 8.38 22.18 0.75 17 6,108,472 8.9
14. use use
used
using 		Verb 10 -6.54 5.03 14.08 0.61 7 12,922,518 4.21
15. can can Verb 35 -5.31 9.33 15.19 0.74 22 4,497,347 12.09
16. could could Verb 23 -3.67 8.23 7.73 0.74 17 5,524,484 9.84
17. may may Verb 16 -3.15 7.16 5.59 0.61 10 12,104,780 4.49
18. leave leaves
leaving
left 		Verb 8 -2.59 5.06 3.52 0.66 8 13,082,561 4.16
19. bring bring
brought 		Verb 5 -2.57 3.54 3.08 0.48 4 33,389,728 1.63
20. need need
needed
needing
needs 		Verb 9 -2.44 5.48 3.29 0.55 6 11,695,817 4.65
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