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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
CHISQ
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# Collocate POS A TTEST MI3 CHISQ JD R AWT fAWT Details Equivalents
1. meet meet
met 		Verb 5 1.1 5.62 2.37 0.34 3 23,672,814 2.3
2. say said
saying
says 		Verb 31 0.85 10.15 0.88 0.71 17 5,803,889 9.37
3. tell tell
tells
told 		Verb 7 0.35 5.82 0.14 0.49 5 14,449,120 3.76
4. feel felt Verb 5 0.1 4.71 0.01 0.4 3 20,096,585 2.7
5. want wanted
wants 		Verb 5 -1.01 4.11 0.7 0.34 3 22,776,497 2.39
6. look look
looked
looks 		Verb 5 -1.8 3.79 1.81 0.17 2 41,368,502 1.31
7. come came
come
coming 		Verb 5 -3.12 3.38 4.12 0.48 4 35,305,565 1.54
8. know knew
know
knows 		Verb 6 -3.58 3.87 5.28 0.43 4 20,568,523 2.64
9. take taken
took 		Verb 5 -4.2 3.12 6.21 0.48 4 15,756,647 3.45
10. make made
make 		Verb 6 -4.64 3.64 7.57 0.6 6 20,007,317 2.72
11. have had
has
have
Having 		Verb 60 -5.87 11 21.84 0.66 22 6,178,790 8.8
12. will will Verb 5 -7.38 2.54 12.94 0.56 5 18,712,539 2.9
13. would Would Verb 5 -8.6 2.37 15.62 0.34 3 22,764,089 2.39
14. do did
do
does
done 		Verb 12 -9.3 5.29 24.53 0.57 7 15,577,290 3.49
15. be 'm
am
are
be
been
being
is
was
were 		Verb 87 -27.16 10.92 282.52 0.79 39 3,247,150 16.74
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