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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 're
's
are
be
been
being
is
was
were 		Verb 409 -41.8 15.74 853.72 0.88 89 490,672 110.79
2. do did
do
does
done 		Verb 22 -30.05 6.03 127.45 0.76 18 8,881,958 6.12
3. have had
has
have 		Verb 149 -19.63 13.06 164.8 0.88 63 1,058,302 51.36
4. would would Verb 18 -16.8 6.03 58.29 0.72 14 6,238,202 8.71
5. take take
taken
takes
taking
took 		Verb 8 -15.91 3.27 38.77 0.54 6 14,213,584 3.82
6. see see
seeing
seen
sees 		Verb 10 -14.7 4.15 38.86 0.66 9 11,674,880 4.66
7. will will Verb 20 -13.25 6.66 45.26 0.75 16 4,946,043 10.99
8. come came
come
comes
coming 		Verb 11 -10 4.91 25.22 0.71 11 11,303,602 4.81
9. could could Verb 13 -9.96 5.49 26.71 0.7 11 11,010,338 4.94
10. give gave
give
given
gives
giving 		Verb 9 -9.74 4.25 22.57 0.64 8 13,678,886 3.97
11. can can Verb 29 -9.47 8.25 33.24 0.73 18 4,821,825 11.27
12. should should Verb 10 -7.38 4.91 16.48 0.66 9 14,055,070 3.87
13. must must Verb 5 -7.31 2.55 12.6 0.56 5 26,930,245 2.02
14. make made
make
makes
making 		Verb 27 -7.12 8.26 21.77 0.75 20 4,404,685 12.34
15. may MAY Verb 14 -5.46 6.32 12.24 0.68 11 8,285,744 6.56
16. mean mean
means
meant 		Verb 7 -4.82 4.12 8.29 0.58 6 16,369,304 3.32
17. need need
needed
needs 		Verb 7 -4.78 4.13 8.18 0.53 5 17,552,330 3.1
18. find find
found 		Verb 13 -4.51 6.23 9.1 0.72 12 7,773,313 6.99
19. become became
become
becomes 		Verb 8 -4.31 4.66 7.4 0.66 8 24,376,197 2.23
20. follow follow
followed
follows 		Verb 5 -3.89 3.19 5.54 0.48 4 33,156,499 1.64
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