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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. be 's
are
be
been
being
is
was
were 		Verb 121 -22.99 12.21 256.29 0.85 54 1,399,388 38.85
2. do did
do
does
doing 		Verb 5 -19.49 1.36 40.85 0.56 5 13,028,241 4.17
3. have had
has
have
having 		Verb 37 -12.96 8.77 59.84 0.76 26 5,457,028 9.96
4. would would Verb 8 -6.58 4.27 13.33 0.61 7 18,765,820 2.9
5. make made
making 		Verb 6 -5.34 3.5 9.12 0.6 6 12,359,608 4.4
6. will will Verb 9 -4.87 4.95 9.25 0.58 7 14,798,914 3.67
7. say said
say
says 		Verb 16 -3.21 7.15 5.86 0.66 10 12,690,642 4.28
8. become became
become 		Verb 9 0.99 6.92 1.49 0.55 6 13,990,565 3.89
9. mean mean
means 		Verb 9 1.04 6.95 1.65 0.68 9 7,691,449 7.07
10. support support
supported
supports 		Verb 5 1.48 6.21 6.51 -0.01 1 53,518,721 1.02
11. accept accept
accepted 		Verb 7 1.97 7.57 15.04 0.26 3 27,737,494 1.96
12. approve approve
approved 		Verb 5 2.02 8.04 43.1 0.48 4 20,567,014 2.64
13. appoint appointed Verb 11 3.11 10.92 154.98 0.5 5 15,181,684 3.58
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