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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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# Collocate POS A TTEST MI3 CHISQ JD R AWT fAWT Details Equivalents
1. force force
forced 		Verb 15 3.35 10.71 83.83 0.72 13 7,747,549 7.02
2. offer offer
offered
offering
offers 		Verb 18 3 10.12 31.02 0.57 9 17,487,574 3.11
3. feature feature
featured
features
featuring 		Verb 10 2.94 10.49 124.85 0.54 7 15,137,550 3.59
4. ski ski
skiing 		Verb 7 2.62 12.37 744.41 0.58 6 13,212,101 4.11
5. favour favoured Verb 5 2 7.88 37.55 0.56 5 17,943,824 3.03
6. set set
setting 		Verb 7 -0.07 5.58 0 0.38 4 25,019,359 2.17
7. must must Verb 10 -0.91 6.28 0.65 0.66 9 8,667,289 6.27
8. may may Verb 10 -3.4 5.59 5.63 0.64 8 9,235,852 5.89
9. should should Verb 7 -4.95 4.09 8.61 0.58 6 32,132,869 1.69
10. use use
used
using 		Verb 6 -6.65 3.28 12.03 0.6 6 13,991,233 3.89
11. come came
come
comes
coming 		Verb 5 -9.68 2.23 17.79 0.48 4 15,588,184 3.49
12. would 'd
would 		Verb 15 -10.03 5.97 28.7 0.69 12 8,879,159 6.12
13. take take
takes
taking
took 		Verb 6 -10.6 2.76 21.4 0.53 5 16,215,955 3.35
14. make made
making 		Verb 8 -10.82 3.73 24.68 0.61 7 13,404,375 4.06
15. could could Verb 5 -10.95 2.08 20.61 0.56 5 17,825,469 3.05
16. will will Verb 10 -11.95 4.39 30.53 0.7 10 8,998,969 6.04
17. know know
known 		Verb 5 -12.44 1.93 23.93 0.56 5 14,815,273 3.67
18. can can Verb 9 -13.08 3.92 32.63 0.64 8 13,198,709 4.12
19. do did
do
does
doing
done 		Verb 18 -18.92 5.89 68.53 0.76 16 10,135,384 5.36
20. have 've
had
has
have
having 		Verb 64 -21.3 10.13 138.11 0.8 32 2,997,037 18.14
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