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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
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# Collocate POS A TTEST MI3 CHISQ JD R AWT fAWT Details Equivalents
1. do do
does
done 		Verb 5 -27.56 0.91 59.57 0.56 5 17,359,027 3.13
2. be 'm
's
are
be
been
being
is
was
were 		Verb 177 -25.25 13.4 329.51 0.86 67 1,000,405 54.34
3. have had
has
have 		Verb 28 -24.74 7.11 120.23 0.77 22 3,559,783 15.27
4. say said
say
says 		Verb 5 -15.45 1.66 30.98 0.48 4 18,108,926 3
5. would would Verb 5 -14.09 1.78 27.84 0.17 2 47,479,509 1.14
6. will will Verb 9 -7.8 4.49 17.27 0.58 7 20,651,536 2.63
7. make made
Make
makes 		Verb 7 -7.24 3.71 14.28 0.38 4 33,366,275 1.63
8. can can Verb 10 -7.18 4.93 16.11 0.52 6 29,879,765 1.82
9. may may Verb 5 -4.06 3.15 5.91 0.48 4 26,198,445 2.07
10. must must Verb 6 -1.11 4.63 0.86 0.6 6 14,390,047 3.78
11. include include
included
includes 		Verb 6 0.66 5.63 0.61 0.6 6 11,770,940 4.62
12. involve involve
involved
involves
involving 		Verb 5 0.98 5.47 1.69 0.56 5 15,832,378 3.43
13. aim aimed
aims 		Verb 5 1.81 7.04 17.34 0.56 5 15,302,858 3.55
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