Skip to main content

Morphological/Inflection Engine for Croatian language, POS tagger, stopwords

Project description

Morphological/Inflection Engine for Croatian language

“text-hr” is Morphological/Inflection Engine for Croatian language written in Python programming language. Includes stopwords and Part-Of-Speech tagging engine (POS tagging) based on inverse inflection algorithm for detection.

Since API is not still freezed, this project is still in alpha.

TAGS

Croatian language, python, natural language processing (NLP), Part-of-speech (POS) tagging, stopwords, inverse inflection, morphological lexicon

OZNAKE

Hrvatski jezik, Python biblioteka, morfologija, infleksija, obrnuta infleksija, prepoznavanje vrsta riječi, računalna obrada govornog jezika, zaustavne riječi, morfološki leksikon

AUTHOR

Robert Lujo, Zagreb, Croatia, find mail address in LICENCE

FEATURES

To name the most important are:
  • inflection system - for producing all forms of one word

  • detection of word types (POS tagging) - from existing list of word forms

  • list of stopwords

System is based on unicode strings, default codepage to convert from and to string is cp-1250.

Check Getting started.

INSTALLATION

Installation instructions - if you have installed pip package http://pypi.python.org/pypi/pip:

pip install text-hr
If not, then old-fashioned way:

GETTING STARTED

There are three important parts that this project provides:

Inflection system

Usage example - start python shell:

> python
>>> from text_hr.verbs import Verb
>>> v = Verb("platiti")
>>> for k in sorted(v.forms.keys()):
...     print k, v.forms[k]
...
AOR/P/1 [u'platismo']
AOR/P/2 [u'platiste']
AOR/P/3 [u'plati\u0161e']
AOR/S/1 [u'platih']
AOR/S/2 [u'plati']
AOR/S/3 [u'plati']
IMP/P/1 [u'platasmo', u'pla\u0107asmo', u'platijasmo']
IMP/P/2 [u'plataste', u'pla\u0107aste', u'platijaste']
IMP/P/3 [u'platahu', u'pla\u0107ahu', u'platijahu']
...
VA_PA//P_O+S+V+N [u'pla\u0107eno']
X_INF// [u'platiti']
X_VAD_PAS// [u'plativ\u0161i']
X_VAD_PRE// [u'plate\u0107i']
X_VAD_PRE// [u'plate\u0107i']

Detection of word types (POS tagging)

TODO: to be done - check test_detect.txt for samples, and detect.py for the logic:

first example in test_detect.txt:

>>> from text_hr.detect import WordTypeRecognizerExample
>>> def test_it(word_list, word_types_filter=None, level=2):
...     wdh = WordTypeRecognizerExample(word_list, silent=True)
...     if not word_types_filter is None:
...         wdh.detect(word_types_filter=word_types_filter, level=level)  # e.g. word_types_filter=["N"]
...     else:
...         wdh.detect(level=level)  # all word types
...     lines_file = LinesFile()
...     wdh.dump_result(lines_file) # doctest: +NORMALIZE_WHITESPACE +ELLIPSIS
...     print "\n".join(lines_file.lines)
...     return wdh

>>> class LinesFile(object):
...     def __init__(self):
...         self.lines = []
...     def write(self, s):
...         self.lines.append(repr(s.rstrip()))

>>> word_list = [
...   "Broj    84"
... , "broji   34"
... , "Brojila  28"
... , "broje   23"
... , "brojeći 22"
... , "brojim   7"
... , "brojimo  5"
... , "brojiš   4"
... , "brojahu  2"
... , "brojaše  1"
... , "brojite  1"
... , "-brijestovu 1"
... , "brijestovi 1"   #the only one checked with endswith, but all other will be checked with get_freq
... , "-brijestove 1"
... , "-brijestova 1"
... ]

Lowest quality, but fastest
>>> wdh = test_it(word_list, level=4) # doctest: +ELLIPSIS
" 10/  183 -> brojati              (u'V-XX_-_JATI-je\\u0107i-0') 84/broj,34/broji,23/broje,22/broje\xe6i,7/brojim,5/brojimo,4/broji\x9a,2/brojahu,1/brojite,1/broja\x9ae"

List of stopwords

TODO: to be simplified and explained in details. this is not tested.

Something like:

from text_hr import word_types

word_types_list = None
for wordobj, l_key, cnt, _suff_id, wform_key, wform in word_types.get_all_std_words(word_types_list):
    if not (wordobj==wordobj_old and l_key==l_key_old):
        wordobj_data["value_base"] = wordobj
        l_key_flds = l_key.split("#")
        # wordobj              l_key                wform_key                      form
        # ondje                FX#ADV#MJE.GDJE                                     ''
        # one                  CH#PRON.OSO#         #P/3F#|A#1                     'njih'
        assert len(l_key_flds)==3, l_key_flds
        is_changeable = (l_key_flds[0]=="CH")
        print "word_type", l_key_flds[1]
        print "subtype",   l_key_flds[2]

    assert wordobj_obj
    # TODO:
    # if wform:
    #     raise NotImplementedError("now wordforms don't hold wf/key, but wf/cnt - it is reduced. Here this is not implemented!!!")

Further

Since there is currently no good documentation, the best source of further information is by reading tests inside of modules and tests in tests directory (dev version). More information in Running tests. And you can allways read a source.

DOCUMENTATION

Sorry but currently there is no good documentation. In progress …

SUPPORT

Since this project is limited with my free time, support will be limited.

REPORT BUG OR REQUEST FEATURE

If you encounter bug, the best is to report it to bitbucket web page http://bitbucket.org/trebor74hr/text-hr.

If there will be an interest for development for other inflection rich languages, I’d be glad to decouple language specific code and create new project that will be capable to deal with multiple languages.

The best way to contact me is by mail (find in LICENCE).

TODO list is in readme.txt (dev version).

CONTRIBUTION

Since this project is not currently in the stable API phase, contribution should wait for a while.

RUNNING TESTS

All tests are doctests (not unittests). There are three type of tests in the package:

  1. doctests in each module - e.g. in verbs.py

  2. doctests in tests/test_*.txt - only development version

  3. tests which are not automatically compared - i.e. in special call mode detect.py can produce output file which needs to be compared manually with some existing file. Such test(s) are very slow. This needs to be changed to be automatic.

Running each module directly will run 1. and 2. if running from development version. To get development version To use development version (http://bitbucket.org/trebor74hr/text-hr):

hg clone https://trebor74hr@bitbucket.org/trebor74hr/text-hr

create text_hr.pth in python site-packages directory with path to text-hr e.g.:

r:\hg-clones\python\text-hr
To run all tests:
  • go to tests directory

  • run tests.py like (with sample output):

    > python tests.py
    testing module   __init__
    testing module   adjectives
    ...
    testing module   word_types
    testing textfile R:\hg-clones\python\text-hr\tests\test_adj.txt
    ...
    testing textfile R:\hg-clones\python\text-hr\tests\test_verbs_type.txt
To run tests for just one module:
  • goto text_hr directory

  • run tests by running module, e.g.:

    > py pronouns.py
    __main__: running doctests
    ..\tests\test_pronouns.txt: running doctests
  • in the case you’re not running from dev version, you’ll get output like this:

    > py pronouns.py
    __main__: running doctests
    ..\tests\test_pronouns.txt: Not found, skipping

TODO

various things, see readme.txt for details.

CHANGES

0.12

ulr1 100608 :
  • README

  • enabled tests from tests.py for all

  • enabled tests from directly from each modules

0.11

ulr1 100607:
  • recreated repo at bitbucket

  • no .suff_registry.pickle and testing_*.out put in zip

0.10

ulr1 100605:
  • first installable release

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

text-hr-0.12.zip (101.5 kB view details)

Uploaded Source

File details

Details for the file text-hr-0.12.zip.

File metadata

  • Download URL: text-hr-0.12.zip
  • Upload date:
  • Size: 101.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for text-hr-0.12.zip
Algorithm Hash digest
SHA256 845a15e8624f2dd50f224b810adfb8cf35489a56b712d0108b0e7bca447bd95e
MD5 8e1503a42ec900b48bd0534aae0434c8
BLAKE2b-256 0e8ab401d758922aecce2d863873ae49ebbd49cdd77a45743dc7d74c5476efcb

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page