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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:
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# Collocate POS A TTEST MI3 CHISQ JD R AWT fAWT Details Equivalents
1. have had
has
have
having 		Verb 13 -19.19 4.74 64.93 0.62 9 10,936,900 4.97
2. do do
does 		Verb 7 -10.38 3.32 22.86 0.58 6 17,495,195 3.11
3. be are
be
been
is
was
were 		Verb 182 -6.17 14.47 39.14 0.82 58 1,469,563 36.99
4. will will Verb 6 -4.39 3.69 7.05 0.53 5 25,051,760 2.17
5. could could Verb 5 -2.39 3.6 2.79 0.56 5 19,189,720 2.83
6. use use
used
using 		Verb 8 0.07 6.03 0 0.61 7 15,763,431 3.45
7. may may Verb 8 0.25 6.14 0.07 0.54 6 10,915,794 4.98
8. require required
requires 		Verb 5 1.42 6.1 5.58 0.4 3 22,732,273 2.39
9. might might Verb 11 2.17 8.45 13.58 0.66 9 19,297,325 2.82
10. arise arise Verb 6 2.2 8.46 47.48 0.15 2 29,002,388 1.87
11. can can Verb 29 2.24 10.49 8.82 0.73 17 6,749,881 8.05
12. must must Verb 13 2.35 8.93 16.04 0.61 8 15,061,189 3.61
13. base base
based 		Verb 12 3.11 10.45 93.74 0.66 10 10,219,046 5.32
14. make made
make
makes
making 		Verb 50 5.16 13.17 99.96 0.78 27 2,964,943 18.33
15. draw draw
drawing
drawn
draws
drew 		Verb 63 7.76 17.47 2,766.6 0.79 30 3,715,086 14.63
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