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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. be 's
are
be
been
being
is
was
were 		Verb 57 -27.98 9.43 249.19 0.77 30 3,519,426 15.45
2. have had
has
have
having 		Verb 35 -8.13 9.01 31.05 0.74 19 6,485,026 8.38
3. will will Verb 6 -4.47 3.67 7.22 0.53 5 12,564,542 4.33
4. see see
seeing
sees 		Verb 5 -3.17 3.37 4.21 0.4 3 23,638,896 2.3
5. come came
come
coming 		Verb 5 -1.99 3.73 2.12 0.56 5 14,787,981 3.68
6. could could Verb 6 -1.82 4.37 1.92 0.53 5 15,203,799 3.58
7. take take
takes
took 		Verb 7 -1.64 4.92 1.68 0.53 5 25,691,322 2.12
8. get get
getting
got 		Verb 9 -1.64 5.71 1.76 0.29 3 45,934,952 1.18
9. turn turned Verb 5 0.96 5.45 1.61 0.48 4 21,580,801 2.52
10. 'd 'd Verb 5 2.18 10 194.4 0.28 2 52,010,337 1.05
11. leave leave
leaves
leaving
left 		Verb 12 2.32 8.77 16.5 0.52 7 14,281,951 3.81
12. park parked Verb 11 3.28 13.58 1,094.17 0.27 2 52,008,882 1.05
13. say said
says 		Verb 42 3.29 11.81 22.54 0.45 11 8,698,130 6.25
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