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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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MI3
CHISQ
JD
R
AWT
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# Collocate POS A TTEST MI3 CHISQ JD R AWT fAWT Details Equivalents
1. be 're
am
are
be
been
being
is
was
were
Verb 315 -58.42 14.5 1,191.53 0.89 81 705,052 77.1
2. do do
does
doing
Verb 14 -43.19 3.97 155.47 0.69 11 11,540,474 4.71
3. have 've
had
has
have
having
Verb 73 -40.48 9.86 318.45 0.84 38 2,947,413 18.44
4. make made
make
makes
Verb 10 -18.65 3.86 51.31 0.7 10 11,369,348 4.78
5. think think
thinking
Verb 6 -16.85 2.19 36.47 0.43 4 24,073,866 2.26
6. can can Verb 19 -15.42 6.31 53.56 0.74 16 8,293,900 6.55
7. take take
taken
takes
taking
Verb 10 -14.9 4.13 39.44 0.66 9 9,179,548 5.92
8. would would Verb 24 -14.74 7.17 55.52 0.75 17 4,652,257 11.68
9. see see
sees
Verb 12 -14.11 4.83 39.86 0.66 9 10,440,164 5.21
10. could could Verb 11 -12.57 4.66 33.44 0.66 9 12,719,006 4.27
11. will will Verb 28 -10.85 8.01 39.43 0.78 21 4,533,611 11.99
12. should should Verb 10 -8.19 4.8 18.87 0.64 8 9,141,461 5.95
13. must must Verb 5 -8.05 2.44 14.18 0.48 4 20,200,911 2.69
14. may may Verb 15 -5.71 6.51 13.29 0.71 12 9,172,907 5.93
15. mean mean
means
meant
Verb 7 -5.4 4.01 9.65 0.58 6 18,146,510 3
16. follow follow
followed
following
follows
Verb 5 -4.36 3.08 6.48 0.56 5 22,156,741 2.45
17. need need
needed
needs
Verb 9 -4.06 5.11 7.03 0.68 9 9,646,046 5.64
18. use use
used
uses
using
Verb 25 -2.97 8.62 5.58 0.78 20 4,661,565 11.66
19. bring bring
brings
brought
Verb 7 -2.63 4.62 3.48 0.53 5 22,480,718 2.42
20. give gave
give
given
gives
giving
Verb 28 -2.49 9.06 4.26 0.79 22 3,486,437 15.59
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