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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
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# Collocate POS A TTEST MI3 CHISQ JD R AWT fAWT Details Equivalents
1. sweep sweep
sweeps
swept
Verb 15 3.82 13.91 999.79 0.74 14 7,007,499 7.76
2. smoke smoke
smokes
smoking
Verb 6 2.39 10.51 231.72 0.6 6 30,917,567 1.76
3. clean clean
cleaned
cleaning
cleans
Verb 5 2.12 8.94 88.19 0.56 5 14,553,765 3.74
4. build build
built
Verb 7 2.01 7.68 16.99 0.53 5 25,812,648 2.11
5. fall fall
falling
falls
fell
Verb 7 1.91 7.47 13.28 0.53 5 12,175,641 4.46
6. rise rises
rising
rose
Verb 5 1.75 6.85 14.21 0.56 5 15,665,623 3.47
7. stand stand
standing
stood
Verb 5 1.27 5.85 3.72 0.56 5 18,846,065 2.88
8. 's 's Verb 6 1.27 6.22 3.34 0.43 4 36,317,360 1.5
9. come came
come
coming
Verb 6 -1.93 4.33 2.1 0.6 6 28,192,703 1.93
10. go go
going
went
Verb 7 -3.69 4.35 5.79 0.26 3 22,069,325 2.46
11. make made
Make
Verb 5 -4.71 3.01 7.27 0.56 5 14,545,922 3.74
12. do did
do
does
done
Verb 5 -15.45 1.66 31.54 0.48 4 20,194,031 2.69
13. have had
has
have
having
Verb 21 -16 6.62 63.56 0.77 18 7,359,689 7.39
14. be 's
are
be
been
is
was
were
Verb 77 -25.92 10.55 254.57 0.84 43 2,006,809 27.09
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