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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:
Collocate's part of speech:
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# Collocate POS A TTEST MI3 CHISQ JD R AWT fAWT Details Equivalents
1. be 's
am
are
be
been
being
is
was
were 		Verb 327 -70.77 14.41 1,527.39 0.91 87 512,622 106.04
2. do did
do
does
doing 		Verb 17 -46.5 4.56 184.11 0.68 13 6,580,017 8.26
3. have 've
had
has
have
having 		Verb 94 -41.65 10.7 365.32 0.88 56 1,276,266 42.59
4. can can Verb 9 -31.16 2.83 87.16 0.55 6 13,182,662 4.12
5. go go
goes
going
gone
went 		Verb 8 -28.45 2.53 74.59 0.66 8 19,221,878 2.83
6. make made
make
makes
making 		Verb 10 -22.76 3.61 64.32 0.66 9 9,212,692 5.9
7. would would Verb 18 -22.71 5.67 83.17 0.77 17 5,466,491 9.94
8. say said
say
saying
says 		Verb 22 -21.73 6.43 86.05 0.79 20 6,287,803 8.65
9. will will Verb 17 -20.5 5.6 71.9 0.75 15 6,464,755 8.41
10. give give
given
gives 		Verb 6 -17.53 2.14 38.08 0.38 3 21,745,993 2.5
11. come came
Come
comes 		Verb 9 -15.86 3.69 40.51 0.68 9 8,076,377 6.73
12. take take
taken
took 		Verb 15 -13.66 5.64 41.81 0.72 13 5,947,580 9.14
13. could could Verb 14 -13 5.45 38.27 0.71 12 7,312,723 7.43
14. may may Verb 10 -10.78 4.5 26.62 0.66 9 9,495,787 5.72
15. must must Verb 7 -7.69 3.65 15.23 0.58 6 16,028,533 3.39
16. see saw
see
seeing
seen 		Verb 34 -6.58 9.09 20.66 0.83 28 3,449,980 15.76
17. leave leave
leaves
leaving
left 		Verb 9 -4.88 4.95 9.13 0.68 9 8,404,397 6.47
18. mean mean
means
meant 		Verb 10 -4.84 5.3 9.32 0.7 10 7,604,620 7.15
19. bring bring
bringing
brought 		Verb 6 -4.32 3.7 6.78 0.53 5 26,279,381 2.07
20. continue continue
continues 		Verb 5 -2.6 3.53 3.14 0.56 5 20,261,625 2.68
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