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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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# Collocate POS A TTEST MI3 CHISQ JD R AWT fAWT Details Equivalents
1. gather gather
gathered
gathering 		Verb 24 4.81 14.93 1,251.37 0.73 16 5,254,011 10.35
2. pit pit
pits
pitted
pitting 		Verb 22 4.69 18.87 21,763.93 0.79 20 5,473,986 9.93
3. keep keep
keeping
kept 		Verb 22 3.73 11.2 68 0.79 20 4,111,484 13.22
4. end end Verb 13 3.26 10.77 109.43 0.72 12 7,898,513 6.88
5. recover recover
recovered
recovering 		Verb 7 2.47 9.52 91.72 0.63 7 9,866,784 5.51
6. sharpen sharpen
sharpened
sharpening 		Verb 6 2.43 12.06 700.71 0.6 6 14,346,782 3.79
7. scare scare
scared
scares
scaring 		Verb 6 2.43 11.98 661.12 0.6 6 12,162,815 4.47
8. scatter scattered
scattering 		Verb 5 2.18 9.88 178.68 0.48 4 17,133,010 3.17
9. use Use
used
uses
using 		Verb 12 0.22 7.26 0.05 0.68 10 14,874,731 3.65
10. take take
taken
takes
took 		Verb 6 -4.13 3.74 6.45 0.53 5 21,379,572 2.54
11. make made
make 		Verb 5 -6.47 2.68 10.94 0.56 5 14,238,196 3.82
12. get get
gets
got 		Verb 5 -6.61 2.66 11.25 0.56 5 23,027,038 2.36
13. have had
has
have
having 		Verb 60 -7.52 10.84 31.97 0.85 40 2,122,095 25.62
14. would would Verb 6 -8.64 2.99 16.88 0.53 5 16,212,867 3.35
15. be 're
's
are
be
been
IS
was
were 		Verb 59 -42 9.07 408.51 0.86 44 2,146,351 25.33
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