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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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Part of speech:
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# Collocate POS A TTEST MI3 CHISQ JD R AWT fAWT Details Equivalents
1. be 's
are
be
been
being
is
was
were 		Verb 343 -69.82 14.59 1,531.31 0.88 81 723,062 75.18
2. do did
do
does
doing
done 		Verb 18 -45.84 4.78 186.14 0.76 16 6,880,570 7.9
3. get get
getting
got 		Verb 5 -35.71 0.56 76.48 0.56 5 14,364,614 3.78
4. have 've
had
has
have 		Verb 140 -31.01 12.4 296.16 0.86 57 1,435,496 37.87
5. would would Verb 14 -27.37 4.56 92.32 0.73 13 6,561,952 8.28
6. say said
say
says 		Verb 20 -23.74 5.99 91.72 0.7 13 9,138,697 5.95
7. go go
goes
going
went 		Verb 12 -22.54 4.26 68.97 0.73 12 6,575,267 8.27
8. can can Verb 17 -21.19 5.56 74.73 0.71 13 6,939,397 7.83
9. see saw
see
seen 		Verb 12 -17.81 4.55 52.45 0.68 10 8,523,440 6.38
10. come came
come
comes
coming 		Verb 9 -16.2 3.66 41.52 0.64 8 14,639,862 3.71
11. take take
taken
taking
took 		Verb 13 -15.57 4.99 46.24 0.74 13 10,035,701 5.42
12. make made
make
makes
making 		Verb 18 -15.43 6.13 52.26 0.73 14 5,379,495 10.1
13. find found Verb 5 -14.82 1.71 29.04 0.56 5 22,021,579 2.47
14. should should Verb 7 -13.78 2.98 30.88 0.63 7 10,095,006 5.38
15. will will Verb 30 -13.39 8.03 53.21 0.77 22 4,601,089 11.81
16. could could Verb 16 -11.94 6.01 36.27 0.74 14 6,953,378 7.82
17. might might Verb 5 -8.29 2.41 14.68 0.56 5 30,768,875 1.77
18. become became
become
becomes 		Verb 7 -7.3 3.7 14.26 0.53 5 14,588,907 3.73
19. may may Verb 16 -7.23 6.51 18.78 0.69 12 8,306,425 6.54
20. use use
used
using 		Verb 18 -7.12 6.92 19.12 0.71 13 5,949,324 9.14
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