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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. bear bear
bearing
bears
bore
borne 		Verb 30 5.3 14.76 866.42 0.81 25 4,680,244 11.61
2. leave leave
leaves
leaving
left 		Verb 33 5.13 13.31 247.02 0.83 29 3,445,572 15.78
3. run ran
running 		Verb 15 3.28 10.53 71.27 0.69 11 12,197,189 4.46
4. heal heal
healed
healing
heals 		Verb 10 3.15 14.43 2,183.75 0.66 9 10,959,828 4.96
5. show show
showed
showing
shows 		Verb 13 2.66 9.33 26.91 0.74 13 6,291,775 8.64
6. carry carried
carries
carry 		Verb 7 1.97 7.59 15.4 0.63 7 9,178,267 5.92
7. prove prove Verb 5 1.86 7.22 20.73 0.56 5 18,180,555 2.99
8. remain remain
remained
remains 		Verb 6 1.83 7.15 13.26 0.53 5 15,012,964 3.62
9. cover cover
covered 		Verb 5 1.75 6.86 14.28 0.56 5 19,991,878 2.72
10. see saw
see
seen 		Verb 9 -0.6 6.08 0.31 0.68 9 10,588,318 5.13
11. get get
getting
got 		Verb 6 -2.63 4.12 3.4 0.6 6 14,410,947 3.77
12. will will Verb 7 -3.08 4.5 4.49 0.63 7 13,596,075 4
13. have 've
had
has
have
having 		Verb 41 -5.21 9.86 16.68 0.81 28 3,474,424 15.65
14. would would Verb 5 -5.4 2.87 8.75 0.56 5 20,124,722 2.7
15. be 's
are
be
is
was
were 		Verb 49 -27.28 8.94 227.67 0.82 31 2,856,768 19.03
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