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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. be 're
's
are
be
been
being
is
was
were 		Verb 388 -53.28 15.31 1,148.21 0.87 82 615,717 88.29
2. do did
do
does 		Verb 12 -50.44 3.21 170.94 0.68 10 8,338,696 6.52
3. have had
has
have
having 		Verb 76 -42.37 9.94 341.67 0.84 43 2,051,795 26.49
4. go go
going
went 		Verb 6 -29.86 1.45 68.89 0.6 6 13,607,210 3.99
5. say said
say
saying
says 		Verb 16 -23.71 5.21 83.33 0.57 10 15,132,592 3.59
6. can can Verb 16 -18.92 5.48 63.86 0.67 11 14,628,707 3.72
7. could could Verb 7 -18.53 2.61 43.49 0.63 7 17,083,486 3.18
8. should should Verb 6 -13.14 2.5 27.39 0.6 6 16,768,508 3.24
9. find find
found 		Verb 5 -12.76 1.9 24.47 0.48 4 16,078,397 3.38
10. take take
taken
takes
taking
took 		Verb 14 -12.49 5.5 36.49 0.66 9 8,381,755 6.49
11. will will Verb 30 -11.1 8.22 41.62 0.73 17 5,047,766 10.77
12. come came
come 		Verb 13 -10.44 5.44 28.31 0.62 8 11,300,375 4.81
13. would would Verb 42 -9.3 9.5 36.42 0.79 26 3,030,943 17.93
14. use use
used
using 		Verb 12 -8.76 5.35 21.98 0.7 11 6,939,538 7.83
15. may may Verb 12 -7.93 5.45 19.29 0.7 11 8,526,240 6.38
16. make made
make
makes
making 		Verb 30 -7.91 8.52 26.07 0.76 23 3,946,466 13.77
17. might might Verb 5 -7.02 2.6 11.96 0.56 5 16,471,510 3.3
18. give gave
give
given
gives
giving 		Verb 16 -6.95 6.55 17.83 0.66 11 9,147,939 5.94
19. see saw
see
seen 		Verb 28 -6.95 8.41 21.18 0.61 13 8,990,280 6.05
20. mean mean
meaning
means 		Verb 6 -6.8 3.25 12.31 0.53 5 22,195,395 2.45
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