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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:
excelSpreadsheet
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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. be 's
am
are
be
been
being
is
was
were
Verb 617 -65.35 16.68 1,762.78 0.8 85 578,949 93.89
2. do did
do
does
Verb 26 -51.97 5.92 252.34 0.61 13 7,711,575 7.05
3. get get
getting
got
Verb 9 -35.73 2.65 100.66 0.58 7 9,750,509 5.58
4. can ca
can
Verb 16 -31.72 4.84 115.19 0.71 13 8,059,631 6.74
5. have 've
had
has
have
having
Verb 224 -31.41 13.98 355.15 0.85 66 1,016,798 53.46
6. say said
say
says
Verb 23 -31.23 6.14 133.31 0.75 15 6,725,465 8.08
7. go go
goes
going
went
Verb 15 -27.98 4.77 97 0.71 13 6,374,403 8.53
8. know knew
know
knowing
known
Verb 12 -24.59 4.15 75.81 0.68 10 19,222,694 2.83
9. use use
used
uses
Verb 6 -24.5 1.71 55.13 0.6 6 16,176,924 3.36
10. could could Verb 10 -24.45 3.52 69.41 0.66 9 10,407,301 5.22
11. would would Verb 34 -21.51 7.95 101.12 0.72 20 5,290,241 10.28
12. will will
wo
Verb 30 -20.36 7.58 89.83 0.76 22 3,555,341 15.29
13. come came
come
comes
Verb 12 -19.31 4.45 57.42 0.73 12 8,882,213 6.12
14. find finds
found
Verb 6 -18.88 2.05 41.27 0.6 6 11,591,663 4.69
15. may may Verb 11 -15.22 4.44 41.86 0.68 10 8,737,931 6.22
16. mean mean
means
meant
Verb 5 -13.55 1.82 26.15 0.56 5 12,825,801 4.24
17. must must Verb 6 -13.12 2.5 27.24 0.6 6 14,575,185 3.73
18. make made
make
makes
making
Verb 37 -12.71 8.79 53.21 0.8 26 5,041,598 10.78
19. feel feel
feels
felt
Verb 5 -11.84 1.99 22.38 0.48 4 19,728,350 2.76
20. work work
worked
working
works
Verb 6 -11.32 2.68 22.91 0.53 5 15,754,772 3.45
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