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Usurper-0.9.1
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مشاهده بیشترتوضیحات
An unsupervised dependency parser.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | OS Independent |
| نام فایل | Usurper-0.9.1 |
| نام | Usurper |
| نسخه کتابخانه | 0.9.1 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Thomas Proisl |
| ایمیل نویسنده | thopro@posteo.de |
| آدرس صفحه اصلی | http://pypi.python.org/pypi/Usurper/ |
| آدرس اینترنتی | https://pypi.org/project/Usurper/ |
| مجوز | GNU General Public License v3 or later (GPLv3+) |
=======
Usurper
=======
Introduction
============
This is an implementation of the unsupervised dependency parser
described by Søgaard (2012). The parser is language independent and
does not need any training data.
The parser operates in two stages. First, it constructs a directed
graph from the words in a sentence using
- information on word adjacency,
- an (automatically created) list of function words [1]_,
- morphological cues
- and information from part-of-speech tags, if available [2]_.
The resulting graph structure is used to rank the words using the
PageRank algorithm (Brin and Page, 1998). In the second stage, the
parser constructs a dependency tree from that ranked list of words. If
part-of-speech information is available, the parser can make use of
universal dependency rules (Naseem et al., 2010).
.. [1] The list of function words is extracted from the whole input
text by applying a variant of Mihalcea and Tarau's (2004)
TextRank algorithm.
.. [2] The parser relies on a universal part-of-speech tagset (Petrov
et al., 2012). The language-dependent input tags are mapped to
that universal tagset using the mappings provided `here
<https://code.google.com/p/universal-pos-tags/>`_.
Installation
============
Usurper can be easily installed using pip::
pip install Usurper
Usage
=====
Using the usrpr executable
--------------------------
You can use the parser as a standalone program from the command
line. Your input text has to be either in `CoNLL-X format
<http://ilk.uvt.nl/conll/>`_ or in a simple format with one token per
line and an empty line between sentences. If your data is
part-of-speech tagged, the tags should be separated from the tokens by
a tab::
Many JJ
people NNS
need VBP
our PRP$
help NN
. .
Please UH
continue VB
our PRP$
important JJ
partnership NN
. .
General usage information, including a list of supported
part-of-speech tagsets, is available via the ``-h`` option::
usrpr -h
If you want to use the full parser, i.e. you have part-of-speech
tagged input data and you want to use the universal dependency rules,
you can invoke the parser like this::
usrpr -t <tag-set> [--conll] <file>
If you do not want to use the universal dependency rules, you can use
the ``--no-rules`` option::
usrpr --no-rules -t <tag-set> [--conll] <file>
If your data is untagged or you want to ignore the tags, simply omit
the ``-t`` option (in that case it is not possible to make use of the
universal dependency rules)::
usrpr [--conll] <file>
Note that the parser tries to automatically identify function
words. If your input file is too small, that cannot be done reliably
and might have an impact on parser performance.
Using the module
----------------
You can easily incorporate the parser into your own Python
projects. All you have to do is import ``usurper.soegaard``::
from usurper import soegaard
parse = soegaard.parse_sentence(tokens, function_words, no_rules, tags, tagset)
The ``parse_sentence`` function returns a `networkx
<https://networkx.github.io/>`_ ``DiGraph`` object. You can convert it
into a nested list representation using the ``export_to_conll_format``
function in ``usurper.utils.conll``.
The function's docstring gives more detailed information about the
arguments it takes::
parse_sentence(tokens, function_words, no_rules, tags=[], tagset=None)
Parse sentence using the algorithm by Søgaard (2012).
Args:
tokens: list of tokens
function_words: set of function words
no_rules: boolean; true if universal dependency rules should
not be used
tags: list of tags, if available; the nth element of tags
should be the part-of-speech tag associated with the nth
element of tokens
tagset: string identifying one of the supported tagsets
Returns:
A networkx DiGraph representing the dependency structure.
Evaluation
==========
Here is a table giving unlabeled attachment scores (ignoring
punctuation) for a couple of languages. Test data for most of the
languages is available from the `CoNLL-X Shared Task website
<http://ilk.uvt.nl/conll/post_task_data.html>`_. Performance for
English was evaluated on section 23 of the Penn Treebank.
========== ======= ======== ===========
Language no tags no rules full parser
========== ======= ======== ===========
Danish 30.04 37.66 38.20
English 20.41 40.74 40.94
German 18.59 33.93 39.24
Portuguese 19.86 44.86 44.50
Slovene 19.70 31.41 31.39
Swedish 20.75 44.69 49.21
========== ======= ======== ===========
References
==========
- Brin, Sergey, Lawrence Page (1998): “The anatomy of a large-scale
hypertextual web search engine.” In: Computer Networks and ISDN
Systems 30/1–7, 107–117. `PDF
<http://infolab.stanford.edu/pub/papers/google.pdf>`__.
- Mihalcea, Rada, Paul Tarau (2004): “TextRank: Bringing order into
text.” In: Proceedings of the 2004 Conference on Empirical Methods
in Natural Language Processing (EMNLP'04). ACL, 404–411. `PDF
<http://www.aclweb.org/anthology/W04-3252>`__.
- Naseem, Tahira, Harr Chen, Regina Barzilay, Mark Johnson (2010):
“Using universal linguistic knowledge to guide grammar induction.”
In: Proceedings of the 2010 Conference on Empirical Methods in
Natural Language Processing (EMNLP'10). ACL, 1234–1244. `PDF
<http://www.aclweb.org/anthology/D10-1120>`__.
- Petrov, Slav, Dipanjan Das, Ryan McDonald (2012): “A universal
part-of-speech tagset.” In: Proceedings of the Eighth International
Conference on Language Resources and Evaluation (LREC'12),
2089–2096. `PDF
<http://www.lrec-conf.org/proceedings/lrec2012/pdf/274_Paper.pdf>`__.
- Søgaard, Anders (2012): “Unsupervised dependency parsing without
training.” In: Natural Language Engineering 18/2, 187–203. `Link
<http://dx.doi.org/10.1017/S1351324912000022>`_.
نحوه نصب
نصب پکیج whl Usurper-0.9.1:
pip install Usurper-0.9.1.whl
نصب پکیج tar.gz Usurper-0.9.1:
pip install Usurper-0.9.1.tar.gz