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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
MI3
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R
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# Collocate POS A TTEST MI3 CHISQ JD R AWT fAWT Details Equivalents
1. work work
working
works 		Verb 22 2.88 10.3 21.7 0.3 4 28,710,654 1.89
2. visit visit
visited
visiting
visits 		Verb 6 1.82 7.13 12.96 -0.01 1 53,479,754 1.02
3. join joined
joining
joins 		Verb 6 1.5 6.54 5.82 0.15 2 27,743,993 1.96
4. run ran
run
running
runs 		Verb 5 -0.15 4.55 0.02 0.4 3 32,608,053 1.67
5. tell told Verb 8 -0.72 5.67 0.42 -0.01 1 54,102,367 1
6. call call
called
calling 		Verb 5 -0.93 4.14 0.62 -0.01 1 54,010,852 1.01
7. become became
become
becomes 		Verb 6 -1.25 4.58 1.04 0.38 3 43,060,258 1.26
8. should should Verb 7 -3.01 4.52 4.27 0.38 4 28,028,453 1.94
9. could could Verb 9 -4.32 5.05 7.74 0.2 3 42,741,034 1.27
10. come came
come
comes 		Verb 6 -5.65 3.45 9.76 0.53 5 22,173,403 2.45
11. say said
say
says 		Verb 17 -6.41 6.82 16.5 0.11 2 27,892,650 1.95
12. would would Verb 11 -8.76 5.05 21.6 0.53 6 23,216,917 2.34
13. will will Verb 9 -8.86 4.36 20.28 0.47 5 16,238,777 3.35
14. can ca
can 		Verb 8 -9.87 3.83 22.17 0.32 3 42,745,459 1.27
15. have had
has
have 		Verb 66 -13.35 10.69 75.17 0.33 12 7,641,023 7.11
16. be are
be
been
being
is
was
were 		Verb 128 -38.45 11.86 503.6 0.33 25 3,655,661 14.87
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