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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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R
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# Collocate POS A TTEST MI3 CHISQ JD R AWT fAWT Details Equivalents
1. be 're
are
be
been
being
is
was
were 		Verb 146 -63.24 11.74 961.09 0.67 50 2,211,316 24.58
2. have had
has
have
having 		Verb 50 -32.81 8.79 212.79 0.69 21 5,992,266 9.07
3. say said
say
says 		Verb 6 -26.2 1.62 60.25 0.6 6 14,282,307 3.81
4. would would Verb 7 -21.83 2.4 52.78 0.63 7 12,786,578 4.25
5. will will Verb 6 -21.02 1.91 47.12 0.43 4 22,777,717 2.39
6. could could Verb 5 -13.63 1.82 26.53 0.56 5 16,367,070 3.32
7. see saw
see
seen
sees 		Verb 11 -9.04 5.02 22.28 0.57 8 15,474,722 3.51
8. become became
become
becomes 		Verb 9 -1.88 5.64 2.19 0.58 7 18,126,441 3
9. produce produced Verb 5 -0.73 4.24 0.4 0.17 2 34,002,095 1.6
10. meet meets
met 		Verb 6 -0.33 4.99 0.1 0.53 5 18,580,724 2.93
11. build build
building
built 		Verb 5 -0 4.64 0 0.56 5 16,563,475 3.28
12. establish establish
established 		Verb 6 0.9 5.83 1.27 0.29 3 24,598,849 2.21
13. cross cross
crossing 		Verb 6 1.84 7.18 13.69 0.53 5 23,771,456 2.29
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