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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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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
are
be
been
being
is
was
were
Verb 142 -20.77 12.84 235.67 0.69 34 2,405,377 22.6
2. get get
gets
got
Verb 5 -6.8 2.63 11.64 0.56 5 25,393,954 2.14
3. can ca
can
Verb 11 -4.18 5.74 7.89 0.55 7 13,426,172 4.05
4. know know
knows
Verb 7 -3.74 4.34 5.89 0.45 4 17,816,413 3.05
5. have had
has
have
having
Verb 89 -3.36 12.51 9.28 0.58 21 4,453,949 12.2
6. make made
make
Verb 12 -2.27 6.44 3.18 0.64 9 8,989,352 6.05
7. say said
say
saying
says
Verb 22 -1.71 8.47 2.21 0.68 13 7,052,006 7.71
8. take take
taken
took
Verb 11 -1.65 6.34 1.84 0.52 6 12,708,401 4.28
9. could could Verb 10 -1.64 6.04 1.79 0.64 8 10,033,494 5.42
10. give gave
given
Verb 8 -1.37 5.43 1.27 0.54 6 17,536,267 3.1
11. do did
do
does
Verb 43 -1.16 10.62 1.19 0.58 15 8,141,833 6.68
12. mean mean
meant
Verb 5 -0.51 4.35 0.21 0.48 4 21,292,059 2.55
13. think think
thinks
thought
Verb 12 -0.47 6.99 0.2 0.52 7 17,810,979 3.05
14. should should Verb 9 -0.45 6.14 0.18 0.5 6 12,068,784 4.5
15. may may Verb 10 -0.22 6.55 0.05 0.37 5 20,365,419 2.67
16. will will Verb 25 0.08 9.31 0.01 0.42 9 8,362,666 6.5
17. might might Verb 6 0.16 5.27 0.03 0.43 4 19,644,288 2.77
18. would 'd
would
Verb 29 0.24 9.78 0.06 0.62 15 6,266,063 8.68
19. see saw
see
seen
sees
Verb 20 0.55 8.83 0.35 0.53 9 8,228,677 6.61
20. find find
found
Verb 11 0.58 7.2 0.41 0.61 8 10,447,601 5.2
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