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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 154 -25.41 12.93 317.38 0.8 64 1,047,245 51.91
2. have had
has
have
having 		Verb 34 -19.11 8.08 95.17 0.8 26 3,244,215 16.76
3. do did
do
does
done 		Verb 8 -18.72 3.07 48.09 0.66 8 8,910,264 6.1
4. would would Verb 7 -9.98 3.36 21.37 0.63 7 12,122,915 4.48
5. can can Verb 7 -8.67 3.52 17.96 0.63 7 23,480,100 2.32
6. should should Verb 5 -3.34 3.33 4.51 0.56 5 31,820,798 1.71
7. provide provide
provided
providing 		Verb 7 0.48 5.9 0.28 0.58 6 11,955,693 4.55
8. lose lost Verb 5 0.87 5.36 1.24 0.56 5 27,755,225 1.96
9. involve involves
involving 		Verb 5 1.08 5.6 2.28 0.48 4 21,604,085 2.52
10. understand understand
understanding
understood 		Verb 5 1.09 5.61 2.34 0.56 5 16,328,366 3.33
11. affect affect
affected 		Verb 5 1.59 6.43 8.74 0.48 4 26,069,563 2.09
12. explain explain
explained
explains 		Verb 10 2.49 8.88 29.17 0.66 9 12,026,020 4.52
13. improve improve
improved
improving 		Verb 19 4.08 12.44 255.33 0.7 14 9,962,221 5.46
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