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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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# Collocate POS A TTEST MI3 CHISQ JD R AWT fAWT Details Equivalents
1. do did
do
does
doing 		Verb 8 -47.38 1.85 132.19 0.57 6 13,911,360 3.91
2. be 're
's
are
be
been
being
is
was
were 		Verb 310 -44.48 14.73 840.72 0.84 72 893,062 60.87
3. say said
say
says 		Verb 7 -29.22 2.02 72.77 0.58 6 12,531,576 4.34
4. would would Verb 10 -21.44 3.68 60.53 0.64 8 11,529,373 4.71
5. make made
make
makes
making 		Verb 8 -16.89 3.2 41.64 0.66 8 10,574,555 5.14
6. take taken
takes
Taking
took 		Verb 6 -16.41 2.23 35.48 0.6 6 15,177,683 3.58
7. have had
has
have
having 		Verb 151 -15.28 13.31 116 0.83 57 1,173,605 46.32
8. see see
seen 		Verb 8 -14.58 3.38 35.07 0.54 6 18,813,473 2.89
9. go go
goes
going
gone
went 		Verb 12 -13.91 4.84 39.32 0.66 9 9,281,143 5.86
10. can can Verb 17 -12.79 6.14 40.75 0.72 13 6,690,663 8.12
11. come came
come
comes
coming 		Verb 7 -11.91 3.16 26.08 0.58 6 16,307,064 3.33
12. will will Verb 23 -9.61 7.46 31.39 0.74 16 5,837,235 9.31
13. may may Verb 8 -7.78 4.09 16.29 0.66 8 8,626,698 6.3
14. could could Verb 15 -7.13 6.31 18.13 0.74 14 6,959,439 7.81
15. use used
uses
using 		Verb 11 -6.4 5.37 14.11 0.68 10 9,376,385 5.8
16. need need
needed
needs 		Verb 5 -5.42 2.87 8.62 0.48 4 28,300,077 1.92
17. might might Verb 5 -4.8 2.99 7.36 0.56 5 13,332,224 4.08
18. mean mean
means
meant 		Verb 7 -3.86 4.32 6.1 0.63 7 13,775,297 3.95
19. bring bringing
brings
brought 		Verb 5 -2.81 3.47 3.51 0.48 4 19,572,334 2.78
20. start start
started
starting 		Verb 5 -2.54 3.55 3.02 0.48 4 27,787,289 1.96
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