Python scripts preprocessing Penn Treebank and Chinese Treebank.
When designing a parser, preprocessing treebanks is a troublesome problem. We need to:
- Split dataset into train/dev/test, following conventional splits.
- Remove xml tags inside CTB.
- Combine the multiline bracketed files into one file, one line for one sentence.
I wondered why there were no open-source tools handling these tedious works. Then I decide to write one myself. Hopefully it will save you some time.
These scripts convert original Penn Treebank (PTB) and Chinese Treebank 5.1 (CTB) corpora into the conventional data setup from Chen and Manning (2014), Dyer et al. (2015). The detailed splits are:
- PTB Training: 02-21. Development: 22. Test: 23.
- CTB Training: 001–815, 1001–1136. Development: 886– 931, 1148–1151. Test: 816–885, 1137–1147.
Let's do it on the fly.
- Python3
- NLTK
Bracketed files parsing relies on NLTK. Please follow NLTK instruction, put BROWN
and WSJ
into nltk_data/corpora/ptb
, e.g.
ptb
├── BROWN
└── WSJ
This script does all the work for you, only requires a path to store output.
usage: ptb.py [-h] --output OUTPUT
Combine Penn Treebank WSJ MRG files into train/dev/test set
optional arguments:
-h, --help show this help message and exit
--output OUTPUT The folder where to store the output
train.txt/dev.txt/test.txt
E.g.
$ python3 ptb.py --output ptb-combined
Importing ptb from nltk
Generating ptb-combined/train.txt
1875 files...
100.00%
39832 sentences.
Generating ptb-combined/dev.txt
83 files...
100.00%
1700 sentences.
Generating ptb-combined/test.txt
100 files...
100.00%
2416 sentences.
The CTB is a little messy, it contains extra xml tags in every gold tree, and is not natively supported by NLTK. You need to specify the CTB root path (the folder containing index.html).
usage: ctb.py [-h] --ctb CTB --output OUTPUT
Combine Chinese Treebank 5.1 fid files into train/dev/test set
optional arguments:
-h, --help show this help message and exit
--ctb CTB The root path to Chinese Treebank 5.1
--output OUTPUT The folder where to store the output
train.txt/dev.txt/test.txt
E.g.
$ python3 ctb.py --ctb corpus/ctb5.1 --output ctb5.1-combined
Converting CTB: removing xml tags...
Importing to nltk...
Generating ctb5.1-combined/train.txt
773 files...
100.00%
16083 sentences.
Generating ctb5.1-combined/dev.txt
36 files...
100.00%
803 sentences.
Generating ctb5.1-combined/test.txt
81 files...
100.00%
1910 sentences.
Then you can start your research, enjoy it!