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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
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# Collocate POS A TTEST MI3 CHISQ JD R AWT fAWT Details Equivalents
1. minister Minister Verb 6 2.42 11.56 490.4 0.53 5 21,430,612 2.54
2. say said
say
says 		Verb 54 2.03 11.98 5.84 0.64 23 4,044,330 13.44
3. laugh laughed Verb 5 1.78 6.92 15.29 -0.01 1 54,342,606 1
4. write writes
written
wrote 		Verb 10 1.65 7.71 5.73 0.7 10 9,397,685 5.78
5. announce announced Verb 5 1.55 6.34 7.74 0.56 5 16,696,639 3.26
6. tell tell
telling
tells
told 		Verb 10 0.3 6.79 0.1 0.66 9 11,610,892 4.68
7. 's 's Verb 5 0.08 4.7 0.01 0.56 5 20,550,153 2.65
8. call called
calls 		Verb 5 -0.62 4.29 0.3 0.56 5 19,280,859 2.82
9. want wanted
wants 		Verb 8 -0.99 5.57 0.73 0.54 6 20,668,097 2.63
10. look looked
looking 		Verb 10 -1.09 6.22 0.89 0.19 3 21,249,280 2.56
11. find find
found 		Verb 6 -2.38 4.19 2.89 0.43 4 17,931,415 3.03
12. think think
thinks
thought 		Verb 9 -2.91 5.36 4.35 0.61 7 23,200,356 2.34
13. see saw
see
seeing
seen 		Verb 12 -3.13 6.24 5.22 0.64 9 10,585,587 5.14
14. come came
come 		Verb 7 -4.1 4.26 6.67 0.58 6 21,417,703 2.54
15. could could Verb 6 -5.62 3.45 9.71 0.6 6 17,475,433 3.11
16. will will Verb 10 -6.96 4.96 15.47 0.64 8 14,339,199 3.79
17. make made
make
makes 		Verb 7 -7.13 3.73 14 0.58 6 14,174,119 3.84
18. take take
takes
took 		Verb 5 -7.34 2.55 12.77 0.56 5 17,882,087 3.04
19. would would Verb 11 -7.56 5.21 17.85 0.64 9 9,797,506 5.55
20. have 'd
've
Had
has
have 		Verb 54 -14.02 9.97 75.39 0.82 33 2,831,622 19.2
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