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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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TTEST
MI3
CHISQ
JD
R
AWT
fAWT
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# Collocate POS A TTEST MI3 CHISQ JD R AWT fAWT Details Equivalents
1. do did
do
does
Verb 8 -23.99 2.75 63.45 0.61 7 25,531,343 2.13
2. be 're
's
are
be
been
being
is
was
were
Verb 258 -20.3 14.84 272.62 0.85 69 911,430 59.64
3. have 'd
've
had
has
have
having
Verb 63 -14.86 10.43 85.72 0.83 32 2,493,877 21.8
4. say said
say
saying
says
Verb 8 -13.09 3.51 31.26 0.66 8 17,500,664 3.11
5. can ca
can
Verb 7 -11.43 3.2 25.1 0.63 7 10,183,334 5.34
6. could could Verb 5 -7.94 2.46 14.05 0.48 4 39,147,281 1.39
7. would would Verb 15 -6.86 6.34 17.39 0.69 12 6,914,175 7.86
8. get get
got
Verb 13 -4.79 6.18 10.04 0.58 8 12,818,081 4.24
9. use use
used
uses
using
Verb 6 -4.58 3.65 7.37 0.6 6 12,582,996 4.32
10. give gave
give
given
giving
Verb 7 -4.08 4.27 6.61 0.63 7 12,977,256 4.19
11. come came
come
comes
coming
Verb 11 -2.88 6.02 4.5 0.68 10 10,891,779 4.99
12. mean mean
means
Verb 5 -1.88 3.76 1.93 0.56 5 24,329,598 2.23
13. should should Verb 10 -1.74 6.01 1.98 0.58 7 11,726,600 4.64
14. may may Verb 14 -0.54 7.42 0.26 0.71 12 7,240,772 7.51
15. provide provide
provided
provides
Verb 6 -0.46 4.92 0.18 0.53 5 17,934,704 3.03
16. follow followed
following
Verb 6 -0.15 5.08 0.02 0.43 4 19,637,719 2.77
17. make made
make
making
Verb 30 0.04 9.82 0 0.64 18 5,308,139 10.24
18. will will
wo
Verb 39 0.34 10.65 0.12 0.73 18 8,225,204 6.61
19. include include
included
Verb 6 0.42 5.44 0.21 0.53 5 16,201,298 3.36
20. lead lead
leading
led
Verb 6 0.56 5.54 0.4 0.6 6 14,638,356 3.71
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