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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
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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 36 -16.78 8.42 82.66 0.76 21 4,388,160 12.39
2. be 's
am
are
be
been
being
is
was
were 		Verb 210 -15.95 14.36 181.35 0.83 68 1,108,154 49.05
3. will will Verb 7 -7.89 3.62 15.96 0.49 5 29,651,571 1.83
4. would would Verb 9 -7.46 4.54 16.36 0.64 8 20,634,818 2.63
5. should should Verb 14 0.61 7.87 0.45 0.47 8 12,407,375 4.38
6. pay paid
pay 		Verb 6 0.81 5.75 0.98 0.43 4 32,183,477 1.69
7. become became
become
becomes
becoming 		Verb 10 0.92 7.14 1.19 0.7 10 10,459,146 5.2
8. sell selling
sold 		Verb 5 1.25 5.82 3.52 0.48 4 23,037,422 2.36
9. die die
died 		Verb 6 1.51 6.56 6.01 0.38 3 29,340,252 1.85
10. succeed succeed
succeeded
succeeding 		Verb 5 1.98 7.78 34.49 0.56 5 14,044,840 3.87
11. leave leave
leaving
left 		Verb 14 2.01 8.72 8.72 0.71 12 9,004,367 6.04
12. institute instituted Verb 7 2.63 12.62 888.24 -0.01 1 54,323,440 1
13. produce produce
produced
producing 		Verb 16 3.2 10.32 51.06 0.72 13 6,632,387 8.2
14. marry married
marry 		Verb 13 3.38 11.43 187.21 0.66 10 8,481,938 6.41
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