Brown Corpus Data for Context Sensitive Spelling Correction

The files have one of three extensions:

.feat files: examples files in the SNoW format.
Each line is a .feat file is an Example:. A list of active features, separated by a , and ends with a :. The class label is considered one of the features. It takes values 0 -- k-1, (where k is the number possible labels, the size of the confusion set). The rest of the features are indexed with numbers above k. The feature indices are sorted and therefore the class label appears as the first in this list.
.occs files: the corresponding raw sentences.
.def files: provide the features definitions we've used (indexed sequentially, starting with k, the confusion set size (here, 2 or 3)). The mapping from raw sentences to the feature based representation is described in the corresponding papers.

Filenames with suffix 20 are test files, those with suffix 80 are the training files (correspond to 20%, 80% of the data, respectively).

Download the entire corpus here.