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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:
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# Collocate POS A TTEST MI3 CHISQ JD R AWT fAWT Details Equivalents
1. be 'M
're
are
be
been
being
is
was
were 		Verb 132 -23.84 12.47 276.8 0.67 28 4,393,872 12.37
2. would would Verb 7 -8.27 3.57 16.98 0.45 4 26,528,421 2.05
3. can can Verb 6 -8.12 3.06 15.61 0.53 5 21,474,746 2.53
4. do did
do
does
doing
done 		Verb 20 -7.32 7.25 21.22 0.58 8 13,268,879 4.1
5. go go
goes
gone
went 		Verb 6 -6.67 3.27 12.18 0.53 5 19,891,227 2.73
6. have had
has
have
having 		Verb 86 -4.29 12.3 14 0.72 21 8,197,882 6.63
7. see see
seeing
seen
sees 		Verb 8 -3.63 4.81 5.87 0.51 5 11,331,194 4.8
8. could could Verb 8 -2.76 5.02 3.92 0.57 6 15,597,845 3.49
9. take take
takes
taking
took 		Verb 9 -2.72 5.41 3.93 0.38 4 26,331,315 2.06
10. make made
make
makes
making 		Verb 12 -2.51 6.38 3.72 0.64 8 13,946,785 3.9
11. should should Verb 6 -1.95 4.32 2.14 0.53 5 24,638,529 2.21
12. give gave
give
given
gives 		Verb 10 -0.75 6.34 0.46 0.66 9 9,931,225 5.47
13. may may Verb 9 -0.71 6.03 0.41 0.64 8 13,529,707 4.02
14. want want
wanted
wants 		Verb 7 -0.62 5.31 0.32 0.45 4 17,100,557 3.18
15. will will Verb 24 -0.33 9.07 0.11 0.59 9 16,331,032 3.33
16. bring bring
bringing
brings
brought 		Verb 5 0.36 4.9 0.16 0.56 5 24,750,318 2.2
17. set set
sets 		Verb 5 0.51 5.02 0.34 0.34 3 23,233,963 2.34
18. try tried
try 		Verb 7 0.67 6.04 0.61 0.49 5 24,029,403 2.26
19. pay paid
pay 		Verb 6 0.94 5.87 1.44 -0.01 1 53,963,073 1.01
20. hope hopes
hoping 		Verb 5 1.3 5.9 4.05 0.34 3 27,982,310 1.94
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