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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
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AWT
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# Collocate POS A TTEST MI3 CHISQ JD R AWT fAWT Details Equivalents
1. run ran
run
running
runs 		Verb 27 4.67 12.82 217.13 0.55 10 10,329,712 5.26
2. base based Verb 16 3.67 11.58 160.86 -0.01 1 54,195,989 1
3. announce announced Verb 5 1.85 7.16 19.49 0.28 2 52,690,900 1.03
4. use use
uses
using 		Verb 15 1.69 8.64 5.12 0.51 6 18,424,005 2.95
5. include include
included
includes 		Verb 5 1.14 5.68 2.67 0.17 2 41,422,357 1.31
6. will will Verb 19 0.2 8.56 0.04 0.34 5 28,269,775 1.92
7. get get
got 		Verb 11 -1.17 6.48 1.03 0.52 5 22,657,641 2.4
8. make made
make
makes 		Verb 10 -1.47 6.09 1.49 0.28 4 25,268,234 2.15
9. can ca
can 		Verb 12 -1.82 6.56 2.21 0.53 6 18,735,699 2.9
10. come came
come
comes 		Verb 5 -2.28 3.63 2.61 0.48 4 17,518,041 3.1
11. see see
seen 		Verb 5 -3.54 3.27 4.93 0.4 3 41,048,082 1.32
12. go Go
going
gone 		Verb 6 -4 3.77 6.19 0.43 4 34,075,296 1.6
13. do did
do
does
done 		Verb 11 -7.92 5.16 19.34 0.57 7 15,536,184 3.5
14. have 've
had
has
have 		Verb 18 -16.71 6.04 63.01 0.5 7 13,096,538 4.15
15. be 'm
're
's
are
be
been
IS
was
were 		Verb 86 -21.66 11.11 210.67 0.46 15 7,362,335 7.38
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