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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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MI3
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# Collocate POS A TTEST MI3 CHISQ JD R AWT fAWT Details Equivalents
1. be 're
's
am
are
be
been
being
is
was
were
Verb 103 -27.35 11.49 303.28 0.85 51 1,606,344 33.84
2. have had
has
have
Verb 40 -12.32 9.08 57.4 0.79 28 3,229,385 16.83
3. can can Verb 5 -8.62 2.36 15.64 0.56 5 13,816,452 3.93
4. will will Verb 6 -7.37 3.17 13.83 0.6 6 15,299,190 3.55
5. make made
make
makes
Verb 5 -6.45 2.69 10.89 0.56 5 12,717,239 4.27
6. see saw
see
seen
Verb 8 -3.23 4.9 4.95 0.57 6 16,655,595 3.26
7. should should Verb 8 -0.75 5.66 0.44 0.66 8 9,811,843 5.54
8. feel feel
felt
Verb 5 -0.15 4.55 0.02 0.56 5 19,510,151 2.79
9. leave leave
leaving
Left
Verb 6 0.16 5.27 0.03 0.53 5 12,818,034 4.24
10. remain remain
remained
remains
Verb 5 1.16 5.7 2.8 0.48 4 20,486,352 2.65
11. tend tend
tended
tends
Verb 5 1.75 6.85 14.24 0.56 5 18,784,746 2.89
12. win win
winning
won
Verb 9 2.28 8.4 21.66 0.58 6 13,523,674 4.02
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