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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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# Collocate POS A TTEST MI3 CHISQ JD R AWT fAWT Details Equivalents
1. be 're
's
am
are
be
been
being
is
was
were 		Verb 448 -73.03 15.46 1,795.81 0.92 94 414,346 131.19
2. do did
do
does
done 		Verb 13 -68.22 3.08 244.27 0.72 12 7,169,268 7.58
3. have 'd
had
has
have
having 		Verb 110 -48.41 11.07 465.42 0.88 60 1,616,391 33.63
4. know know
known
knows 		Verb 7 -30.05 1.99 74.17 0.63 7 16,458,207 3.3
5. say said
say
says 		Verb 20 -29.9 5.7 119.46 0.72 15 5,985,880 9.08
6. would would Verb 22 -25.56 6.23 103.79 0.78 19 4,956,986 10.97
7. get get
gets
getting
got 		Verb 14 -23.89 4.73 78.68 0.68 11 8,660,889 6.28
8. look looked
looking 		Verb 5 -21.41 1.24 43.75 0.56 5 26,020,110 2.09
9. could could Verb 11 -20.12 4.1 58.05 0.68 10 10,646,329 5.11
10. take take
taken
takes
taking
took 		Verb 15 -17.88 5.32 57.75 0.71 13 7,707,512 7.05
11. make made
make
makes
making 		Verb 22 -17 6.71 63.59 0.78 19 5,469,604 9.94
12. go go
goes
going
gone
went 		Verb 25 -16.95 7.15 66.72 0.76 18 5,416,339 10.04
13. can ca
can 		Verb 36 -15.19 8.52 66.8 0.78 23 3,096,818 17.55
14. may may Verb 10 -14.14 4.19 36.9 0.66 9 9,352,047 5.81
15. will will Verb 40 -13.59 8.99 59.95 0.8 28 4,387,544 12.39
16. use use
used
uses
using 		Verb 13 -12.69 5.22 35.99 0.72 12 8,919,278 6.09
17. mean meaning
means 		Verb 5 -11.81 1.99 22.33 0.48 4 20,685,798 2.63
18. find find
finding
found 		Verb 10 -11.54 4.43 28.88 0.66 9 8,152,658 6.67
19. must must Verb 6 -11.4 2.67 23.14 0.6 6 20,179,759 2.69
20. give gave
give
given
gives
giving 		Verb 16 -11.18 6.08 33.3 0.72 13 5,425,705 10.02
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