Amruta Purandare has been doing some experiments with the Ngram Statistics
Package and the English GigaWord corpus lately. As a by-product of this
work she found herself with files that contain bigram counts for the 4
individual corpora that make up the GigaWord corpus, as well as counts for
the combined  corpus. (The total number of words in the GigaWord corpus is
well over 1 billion.)

Since it took her a little while to create these files (about 3 days for
all the data on a 3GhZ Pentium) we thought it might be useful to make this
data available for download. To be clear, we aren't providing the GigaWord
corpus  here, just the counts of bigrams that occur in the corpus.

You can find the bigram counts of the English GigaWord data at:

http://www.d.umn.edu/~tpederse/nsp.html

Below you'll find the README for this data. Let us know if you have
any questions or comments.

Enjoy,
Ted and Amruta

=========================================================================
=========================================================================

                    README file for bigram counts
                      of English GigaWord corpus
                   ===============================

This package contains the counts of bigrams that occur more than 1 time
in the English GigaWord Corpus. These counts were found using the
huge-count.pl utility program that is a part of the Ngram Statistics
Package (version 0.69).

The English GigaWord corpus is distributed by LDC, and consists of 4
sources of news text, which are identified as nyt, xie, apw, and afe.

- Agence France Press English Service          (afe)
- Associated Press Worldstream English Service (apw)
- The New York Times Newswire Service          (nyt)
- The Xinhua News Agency English Service       (xie)

The sum total of these files is over 1 billion words. You can find out
more about GigaWord at:

http://wave.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2003T05

Four input files were created (one for each of the corpora above, plus
the concatenation of these four files which we call "giga"). This data was
created as follows:

1) Text between <p> and </p> tags was extracted for each corpora and saved
into a file named as apw, afe, xie, or nyt.

2) The extracted text was converted to lower case.

3) The separate files (apw, afe, xie, nyt) were concatenated into a single
file (giga).

4) Bigram counts are obtained by huge-count.pl as follows:

Each of the five files (apw, afe, xie, nyt, giga) were processed by
huge-count.pl as follows:

        huge-count.pl --newLine --stop stoplist.new --nontoken nontoken.regex --token 
token.regex --remove 2 --split 500 $input-count $input

The file name is the value of $input. The value of --split was 500 for
giga, and 100 for apw, afe, xie, and nyt. The stoplist, token, and
nontoken files used are provided in this distribution. The output of
huge-count are the bigram counts found in the files :

        apw-count, nyt-count, afe-count, xie-count, and giga-count.

5) Note that a user could create co-occurrence counts from this data using
the NSP utility program combig.pl as follows:

        combig.pl $input-count > $input-cocs

Bigrams are two word sequences that occur in a given order, while
co-occurrences are two word sequences that occur next to each other
without regard to any ordering.

--
Ted Pedersen
http://www.d.umn.edu/~tpederse


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