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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. be 's
are
be
been
being
is
was
were 		Verb 584 -38.06 17.02 842.9 0.83 86 550,773 98.7
2. have had
has
have
having 		Verb 139 -27.73 12.49 255.8 0.83 55 1,215,453 44.72
3. do did
do
does
done 		Verb 36 -26.55 7.9 135.87 0.8 26 3,352,338 16.22
4. go go
goes
going
gone
went 		Verb 9 -24.6 3.14 67.02 0.68 9 8,304,446 6.55
5. say said
say
says 		Verb 17 -24 5.4 86.7 0.72 13 5,818,883 9.34
6. know knew
know
known 		Verb 7 -22.01 2.39 52.77 0.58 6 15,635,115 3.48
7. make made
make
makes 		Verb 12 -18.68 4.49 55.56 0.7 11 11,042,566 4.92
8. use use
used
using 		Verb 6 -15.64 2.29 33.46 0.53 5 13,133,149 4.14
9. take take
taken
takes
Taking
took 		Verb 13 -14.02 5.11 40.78 0.72 12 9,184,158 5.92
10. look look
looked
looks 		Verb 6 -13.83 2.44 29.05 0.6 6 16,749,137 3.25
11. can can Verb 30 -12.03 8.14 46.29 0.78 22 4,679,917 11.62
12. could could Verb 15 -11.26 5.85 32.89 0.68 11 8,634,904 6.3
13. would would Verb 38 -11.19 9 45.6 0.8 26 3,496,100 15.55
14. will will
wo 		Verb 33 -10.79 8.56 41.35 0.81 24 3,418,066 15.9
15. may may Verb 9 -10.76 4.14 25.48 0.68 9 12,310,877 4.42
16. come came
come
comes 		Verb 15 -9.8 5.99 27.54 0.61 9 13,047,622 4.17
17. see saw
see
seen
sees 		Verb 26 -8.18 8.02 26.11 0.65 10 9,003,834 6.04
18. give gave
give
given
gives
giving 		Verb 15 -7.95 6.2 20.94 0.69 12 9,184,880 5.92
19. put put Verb 6 -7.67 3.12 14.33 0.43 4 20,327,828 2.67
20. work work
worked
works 		Verb 6 -6.79 3.25 12.29 0.6 6 19,909,662 2.73
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