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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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TTEST
MI3
CHISQ
JD
R
AWT
fAWT
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# Collocate POS A TTEST MI3 CHISQ JD R AWT fAWT Details Equivalents
1. have had
has
have 		Verb 26 -22.81 6.95 106 0.68 14 7,218,711 7.53
2. do did
do
does 		Verb 7 -19.91 2.52 48.59 0.35 3 37,104,702 1.47
3. be am
are
be
been
being
is
was
were 		Verb 197 -18.69 14.02 224.47 0.66 35 2,808,465 19.36
4. would would Verb 7 -9.71 3.39 20.68 0.53 5 14,990,327 3.63
5. can can Verb 13 -4.52 6.23 9.27 0.53 7 24,948,613 2.18
6. see see Verb 8 -4.49 4.63 7.9 0.51 5 18,007,280 3.02
7. use use
used
using 		Verb 5 -3.82 3.21 5.44 0.34 3 21,224,450 2.56
8. could could Verb 8 -3.5 4.84 5.55 0.34 4 15,811,436 3.44
9. take take
taken
takes
taking
took 		Verb 10 -2.98 5.69 4.63 0.49 5 33,455,859 1.62
10. make made
make
makes
making 		Verb 18 -1.28 7.96 1.28 0.7 13 7,380,526 7.37
11. must must Verb 6 -0.74 4.79 0.43 0.48 4 27,674,770 1.96
12. should should Verb 10 -0.7 6.36 0.4 0.28 4 39,303,638 1.38
13. will will Verb 26 -0.59 9.24 0.32 0.68 14 9,912,154 5.48
14. call called Verb 5 -0.35 4.43 0.11 0.56 5 18,827,879 2.89
15. may may Verb 14 0.37 7.77 0.16 0.6 9 12,046,926 4.51
16. appear appear
appears 		Verb 5 0.74 5.22 0.82 0.48 4 27,506,994 1.98
17. run run
running 		Verb 7 1 6.3 1.6 0.23 2 50,766,366 1.07
18. agree agreed
agrees 		Verb 5 1.1 5.62 2.37 0.34 3 43,520,182 1.25
19. keep keep
keeps 		Verb 9 1.19 7.07 2.35 0.47 5 17,916,792 3.03
20. increase increase
increased
increases 		Verb 5 1.28 5.88 3.88 0.48 4 15,368,396 3.54
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