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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. contain contain
contained
containing
contains
Verb 15 3.32 10.63 78.05 0.49 8 11,495,355 4.73
2. resolve resolve
resolving
Verb 11 3.17 11.43 228.87 0.71 11 10,455,366 5.2
3. explain explain
explained
explaining
explains
Verb 10 2.46 8.82 27.31 0.7 10 9,069,900 5.99
4. involve involve
involved
involves
Verb 10 2.31 8.54 19.9 0.46 6 23,317,900 2.33
5. ignore ignore
ignored
Verb 5 1.86 7.2 20.37 0.56 5 13,513,200 4.02
6. arise arises
arising
arose
Verb 5 1.73 6.79 13.27 0.48 4 19,635,277 2.77
7. throw throw
thrown
throws
Verb 5 1.66 6.6 10.73 0.56 5 15,044,253 3.61
8. remain remain
remains
Verb 5 0.85 5.33 1.17 0.56 5 14,620,865 3.72
9. see saw
see
seeing
seen
sees
Verb 18 -0.96 8.05 0.76 0.76 16 5,502,215 9.88
10. find find
finds
found
Verb 7 -1.67 4.91 1.72 0.63 7 11,249,514 4.83
11. may may Verb 8 -1.92 5.25 2.22 0.61 7 18,454,851 2.95
12. come came
come
comes
Verb 6 -4.59 3.65 7.42 0.6 6 10,970,315 4.96
13. can can Verb 13 -5.06 6.14 10.87 0.74 13 6,823,740 7.97
14. could could Verb 5 -6.3 2.71 10.53 0.56 5 24,189,473 2.25
15. would would Verb 8 -9.49 3.88 21.18 0.54 6 12,746,745 4.26
16. will will Verb 5 -11.6 2.01 22.21 0.34 3 18,018,437 3.02
17. be 'm
's
am
are
be
been
being
is
was
were
Verb 232 -16.91 14.64 203.04 0.9 73 832,330 65.31
18. do did
does
Verb 5 -26.2 0.97 56.43 0.56 5 18,268,443 2.98
19. have had
has
have
Verb 20 -29.45 5.72 127.47 0.77 18 7,351,994 7.39
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