A Python module for interfacing with the Treetagger by Helmut Schmid.
Copyright (C) 2018 Mirko Otto
For license information, see LICENSE.txt
- TreeTagger (The names of the parametres Files of the TreeTagger program have changed, use the version after the 16th of October 2018; Since October 2020, it seems that the data must now be transferred to the TreeTagger programme as files.)
- Python 3
- NLTK
- treetagger.py is for Python 3
Tested in June 2021 with TreeTagger 3.2.3 (versions after October 2020), Python 3.9.5 and NLTK 3.6.2 on Ubuntu 20.04, OSX 10.15 and Windows 10
The TreeTagger is a copyrighted software by Helmut Schmid and IMS, please read the license agreement before you download the TreeTagger package and language models.
Before you can use the treetagger-python package please ensure you
have downloaded and installed the
TreeTagger
itself.
After installing the TreeTagger program, please check if it works properly.
The treetagger-python package now checks the installed language packs "language-utf8.par" in the lib directory. You can use the get_installed_lang function to show the languages. The corresponding executable files are used in the cmd directory under Linux and in the bat directory under Windows.
The English tagging examples and the Python doctest show the result with the "English parameter file (PENN tagset)" file.
Make sure that you know the HOME directory of the TreeTagger program.
To use the Python package treetagger-python, you must either set the environment variable TREETAGGER_HOME or the path path_to_treetagger when the program is called. In section usage you can see the second option.
To set the environment variable TREETAGGER_HOME, enter the path to the installation directory of TreeTagger:
export TREETAGGER_HOME='/path/to/your/TreeTagger/'
Clone the repository and change to this directory. In this directory the Python package treetagger-python can be used without installation.:
clone https://github.com/miotto/treetagger-python.git cd treetagger-python
Initialize by specifying the path path_to_treetagger:
from treetagger import TreeTagger tt = TreeTagger(path_to_treetagger='/path/to/your/TreeTagger/')
Show the installed languages:
from treetagger import TreeTagger tt = TreeTagger(path_to_treetagger='/path/to/your/TreeTagger/') tt.get_installed_lang()
The output could look like this
['english', 'german']
Tagging a sentence from Python:
from treetagger import TreeTagger
tt = TreeTagger(path_to_treetagger='/path/to/your/TreeTagger/')
tt.tag('What is the airspeed of an unladen swallow?')
The output is a list of [token, tag, lemma]:
[['What', 'WP', 'what'], ['is', 'VBZ', 'be'], ['the', 'DT', 'the'], ['airspeed', 'NN', 'airspeed'], ['of', 'IN', 'of'], ['an', 'DT', 'an'], ['unladen', 'JJ', '<unknown>'], ['swallow', 'NN', 'swallow'], ['?', 'SENT', '?']]
Tagging a german sentence from Python:
from treetagger import TreeTagger
tt = TreeTagger(path_to_treetagger='/path/to/your/TreeTagger/', language='german')
tt.tag('Das Haus hat einen großen hübschen Garten.')
The output is a list of [token, tag, lemma]:
[['Das', 'ART', 'die'], ['Haus', 'NN', 'Haus'], ['hat', 'VAFIN', 'haben'], ['einen', 'ART', 'eine'], ['großen', 'ADJA', 'groß'], ['hübschen', 'ADJA', 'hübsch'], ['Garten', 'NN', 'Garten'], ['.', '$.', '.']]
Initialize by specifying the path path_to_treetagger:
from treetagger import TreeTaggerChunker ttc = TreeTaggerChunker(path_to_treetagger='/path/to/your/TreeTagger/')
Show the installed languages:
from treetagger import TreeTaggerChunker ttc = TreeTaggerChunker(path_to_treetagger='/path/to/your/TreeTagger/') ttc.get_installed_lang()
The output could look like this
['english', 'german']
Chunk a sentence from Python:
from treetagger import TreeTaggerChunker
ttc = TreeTaggerChunker(path_to_treetagger='/path/to/your/TreeTagger/')
ttc.parse('What is the airspeed of an unladen swallow?')
The output is a list of a chunk structure with [token, tag, lemma]:
[['<NC>'], ['What', 'WP', 'what'], ['</NC>'], ['<VC>'], ['is', 'VBZ', 'be'], ['</VC>'], ['<NC>'], ['the', 'DT', 'the'], ['airspeed', 'NN', 'airspeed'], ['</NC>'], ['<PC>'], ['of', 'IN', 'of'], ['<NC>'], ['an', 'DT', 'an'], ['unladen', 'JJ', '<unknown>'], ['swallow', 'NN', 'swallow'], ['</NC>'], ['</PC>'], ['?', 'SENT', '?']]
Chunk a sentence in a tree from Python:
from treetagger import TreeTaggerChunker
ttc = TreeTaggerChunker(path_to_treetagger='/path/to/your/TreeTagger/')
ttc.parse_to_tree('What is the airspeed of an unladen swallow?')
The output is a chunk structure as a nltk tree:
Tree('S', [Tree('NC', [Tree('What', ['WP'])]), Tree('VC', [Tree('is', ['VBZ'])]), Tree('NC', [Tree('the', ['DT']), Tree('airspeed', ['NN'])]), Tree('PC', [Tree('of', ['IN']), Tree('NC', [Tree('an', ['DT']), Tree('unladen', ['JJ']), Tree('swallow', ['NN'])])]), Tree('?', ['SENT'])])
Chunk a sentence in a tree from Python:
from nltk.tree import Tree
from treetagger import TreeTaggerChunker
ttc = TreeTaggerChunker(path_to_treetagger='/path/to/your/TreeTagger/')
ttc_tree = ttc.parse_to_tree('What is the airspeed of an unladen swallow?')
print(ttc_tree)
The output is a chunk structure as a nltk tree:
(S (NC (What WP)) (VC (is VBZ)) (NC (the DT) (airspeed NN)) (PC (of IN) (NC (an DT) (unladen JJ) (swallow NN))) (? SENT))