Natural language data loading tools
natlang: Natural Language Data Loading Tools
Data loader/common data structures and other tools
Most of the code are Python2/3 compatible. For the version of python for specific modules, please check the second line of each source file.
Install using pip will get you the latest tested version of
> pip install natlang
Alternatively, you can also install from source using the following command:
> python setup.py install
If you want to load up a dataset, then just do this:
> import natlang as nl > data = nl.load(filePattern, format=ChoosenFormat) > # ChoosenFormat here can be an actual imported format or string. > # Alternatively, you can also pass a loader func in using nl.load(filePatttern, loader=func)
For parallel datasets:
> import natlang as nl > data = nl.biload(srcPattern, tgtPattern, srcFormat, tgtFormat) > # Loader option similar to nl.load also applies here. src stands for source, tgt stands for target.
All supported formats are placed under
Currently the following formats are tested:
txt: simple text format. Sentences are separated by
\n, tokens/words are separated by whitespace.
tree: constituency tree format. Run
python -i format/tree.pyto play around.
semanticFrame: Propbank/Nombank frame loader. Returns bundles of frames for analysis.
AMR: Abstract Meaning Representation. Run
python -i format/AMR.pyto play around.
conll: General CoNLL format loader. Default is CoNLL_U. Run
python -i format/conll.pyto play around.
1.1 Recommended Functions
For formats supporting being loaded from a file, one should implement a
function in the format file (see 2.1).
For formats supporting being exported, each instance of that format should have
export method that outputs a string.
2.1 Individual Loader
Each format has its own loader.
It is defined as
load function has the following interface:
def load(file, linesToLoad=sys.maxsize)
At test time, the
load function would be expected to parse the file
description and read from it.
It will return the first
linesToLoad entries as a list.
For example, if one wishes to use load a file in constituency tree format (see
tests/sampleTree.txt), one could do the following:
from datatool.format import tree x = tree.load("datatool/tests/sampleTree.txt")
This class allows one to load parallel corpora (L1, L2) in any format. You can specify the format for L1 and L2 side separately.
from datatool.loader import ParallelDataLoader loader = ParallelDataLoader(srcFormat='txtOrTree', tgtFormat='txtOrTree')
'txtOrTree' is the default value for
Note that under the
format folder, except for data structures for specific
formats, there are also mere loaders and
'txtOrTree' is one that can handle
After initialising the loader, one can just go ahead and run:
loader.load(fFile, eFile, linesToLoad)
The loader will automatically align the parallel text and output a list of
tuples, each containing a single entry in L1 and L2.
Entries with either L1 or L2 being
None or of length 0 will be omitted.
from datatool.exporter import exportToFile, RealtimeExporter
txt format dataset or
tree format dataset (not single entry, but
rather a dataset) to file.
The code is pretty self-explanatory. If the export function of a specific format takes quite a bit of time, this method is recommended.
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