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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
am
are
be
been
being
is
was
were
Verb 223 -34.7 13.87 542.8 0.8 56 1,399,388 38.85
2. do did
do
does
Verb 16 -20.07 5.41 69.97 0.62 11 6,995,594 7.77
3. have had
has
have
having
Verb 73 -18.33 10.73 119.15 0.75 29 3,351,798 16.22
4. say said
say
says
Verb 9 -16.05 3.67 41.65 0.64 8 10,434,420 5.21
5. go go
goes
going
gone
went
Verb 7 -12.78 3.07 28.54 0.58 6 13,337,846 4.08
6. could could Verb 5 -10.69 2.11 20.02 0.48 4 25,032,970 2.17
7. see saw
see
seen
Verb 7 -9.97 3.36 21.17 0.63 7 15,002,152 3.62
8. get get
gets
getting
got
Verb 10 -8.99 4.7 21.41 0.56 6 17,160,687 3.17
9. come came
come
Verb 6 -8.21 3.05 15.67 0.43 4 17,616,946 3.09
10. can can Verb 17 -7.34 6.7 19.81 0.72 14 5,432,935 10.01
11. would would Verb 20 -7.32 7.24 20.83 0.65 11 8,935,928 6.08
12. make made
make
makes
making
Verb 15 -5.89 6.48 14.01 0.56 10 8,833,779 6.15
13. give given
gives
giving
Verb 7 -5.89 3.93 10.86 0.49 5 14,129,206 3.85
14. use use
used
using
Verb 8 -4.89 4.55 8.86 0.57 6 11,623,891 4.68
15. must must Verb 5 -3.41 3.31 4.62 0.56 5 11,540,910 4.71
16. take take
takes
taking
took
Verb 18 -3.14 7.54 5.75 0.67 12 7,867,345 6.91
17. will will Verb 30 -3.07 9.17 6.18 0.72 16 5,902,169 9.21
18. should should Verb 12 -2.22 6.46 3.03 0.64 9 7,841,611 6.93
19. might might Verb 6 -1.91 4.34 2.05 0.43 4 20,437,315 2.66
20. may may Verb 18 -0.55 8.16 0.27 0.73 15 6,164,827 8.82
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