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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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MI3
CHISQ
JD
R
AWT
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# Collocate POS A TTEST MI3 CHISQ JD R AWT fAWT Details Equivalents
1. have had
has
have
having 		Verb 25 -20.13 6.96 89.88 0.79 22 6,934,346 7.84
2. be 's
are
be
been
being
is
was
were 		Verb 162 -19.13 13.36 219.06 0.9 74 765,279 71.03
3. would would Verb 5 -10.67 2.11 20.2 0.56 5 14,475,736 3.76
4. say said
say
says 		Verb 6 -10.32 2.79 20.96 0.6 6 16,296,029 3.34
5. will will Verb 5 -9.22 2.29 16.95 0.56 5 17,229,142 3.16
6. make made
make
makes
making 		Verb 6 -6 3.38 10.61 0.53 5 12,212,249 4.45
7. see see
seen
sees 		Verb 5 -5.93 2.77 9.78 0.56 5 15,440,521 3.52
8. may may Verb 8 -1.11 5.52 0.89 0.61 7 11,681,727 4.65
9. affect affect
affected 		Verb 5 1.68 6.64 11.27 0.34 3 25,570,182 2.13
10. remain remain
remained
remains 		Verb 10 2.35 8.61 21.6 0.66 9 14,842,982 3.66
11. change change
changed
changes 		Verb 11 2.53 8.99 26.96 0.64 9 11,446,938 4.75
12. broaden broaden
broadened
broadening 		Verb 9 2.98 13.35 1,143.07 0.68 9 10,188,361 5.34
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