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noun_phrase
stringlengths
0
702
count
int64
1
249k
you
249,233
it
200,413
I
188,033
we
115,472
that
110,507
they
69,234
he
51,780
which
48,012
this
46,567
what
39,533
who
39,492
them
33,159
us
26,247
me
25,692
she
25,001
all
17,793
time
16,945
people
15,966
him
12,069
something
9,705
some
9,336
those
8,471
world
8,011
part
7,471
lot
7,310
-
7,272
way
6,542
her
6,345
order
6,171
place
6,004
information
5,955
life
5,884
others
5,805
things
5,800
everything
5,775
these
5,500
work
5,393
number
5,351
day
5,327
company
5,261
God
5,211
students
5,200
fact
5,055
use
4,952
end
4,893
someone
4,867
money
4,792
everyone
4,668
home
4,567
example
4,524
addition
4,392
children
4,326
anything
4,315
yourself
4,295
water
3,981
year
3,933
anyone
3,805
case
3,788
services
3,742
business
3,691
course
3,690
nothing
3,618
years
3,465
data
3,447
game
3,429
top
3,391
one
3,391
Thanks
3,384
city
3,334
person
3,257
book
3,157
itself
3,134
themselves
3,048
women
2,990
service
2,990
country
2,983
house
2,972
each
2,932
school
2,923
process
2,910
state
2,883
experience
2,821
access
2,800
result
2,789
variety
2,788
site
2,783
event
2,738
family
2,721
myself
2,712
future
2,683
mind
2,654
love
2,651
sale
2,640
University
2,618
both
2,614
any
2,613
2,572
United States
2,569
team
2,566
problem
2,562
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Noun Phrases Dataset

This dataset contains noun phrases extracted from allenai/c4.

It includes two configurations: uncased and cased, with 1 895 908 and 2 000 002 entries, respectively.

JSONL Fields

Each entry contains:

  • noun_phrase: The extracted noun phrase.
  • count: Frequency of occurrence.

Example Rows

{"noun_phrase": "ship invoices", "count": 1}
{"noun_phrase": "\"river", "count": 1}
{"noun_phrase": "no boiler system", "count": 1}

Construction

  • Cased Data: Original noun phrases with preserved casing.
  • Uncased Data: Constructed by normalizing cased data to lowercase, aggregating counts for identical phrases, and retaining the original phrase with the highest count.

Preprocessing and Extraction

  • Preprocessing: Unicode normalization, bracket removal, bullet point standardization, quotation mark normalization, and whitespace normalization.
  • SpaCy: Noun phrase extraction using the "en_core_web_sm" model. Articles such as "a" or "the" were removed.

Original Data Source

The C4 dataset is a cleaned version of the Common Crawl dataset, providing a comprehensive source of English text for linguistic analysis and NLP tasks.

Applications

Suitable for grammar analysis, linguistic studies, and natural language processing (NLP) tasks.

Dataset Details

  • Language: English (en)
  • Licence: Open Data Commons License
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