Cross-platform ENIAM with useful bindings 🚀

This project provides only a wrapper for ENIAM (see online source code) Author of original code is Wojciech Jaworski.

Using eniam library

1. First, you have to install eniam by calling pip install eniam
2. Then you can try parsing some example phrases (see examples/example.ipynb):

# !pip install opencv-python
# !pip install camelot-py
# !pip install wand
from eniam import *

dom_result = Eniam(['KOT', 'MYSZ'], {
    rule(lemma='kot',pos=subst,case=nom):     gram('KOT'),
    rule(lemma='gonić',pos=fin,person=ter):   (ip<gram('KOT'))>gram('MYSZ'),
    rule(lemma='mysz',pos=subst,case=acc):    gram('MYSZ'),
    root_rule():                                  s % ip,
}, ['KOT', 'MYSZ', 'ZDARZENIE'], {
    valence_rule('kot', 'noun'): 'KOT',
    valence_rule('mysz', 'noun'): 'MYSZ',
    valence_rule('gonić', 'verb'): 'ZDARZENIE',
}).dom("Kot goni mysz.")

dom_result.show()

Eniam syntax

The eniam library uses custom primitive AST the most of the operations looks exactly the same as in normal ENIAM convensions except for those modifications:

1. / is replaced with >
2. \ is replaced with <
3. ip{ |x1, |x2, |x3... |xn} is replaced with ip[ x1 | x2 | ... | xn]
4. ?x is replaced with function optional(x)
5. a\?(x) is replaced with a % x
6. the grammar can contain inline literals created using gram() function for example rule(lemma='kot',pos=subst): gram('np/np\\np'), would be a valid rule.

Useful methods

1. Showing the result in Jupyter notebook Eniam(...).dom("Kot goni mysz.").show()
2. Getting the html code Eniam(...).dom("Kot goni mysz.").html()
3. Saving the html code Eniam(...).dom("Kot goni mysz.").save_html('output_file')
4. Multiple input sentences
5. Showing the result in Jupyter notebook Eniam(...).dom(["Kot goni mysz.", "Mysz goni kota."]).show()

Using raw ENIAM interface

Running inside docker

To run ENIAM docker please use the following commands:

    # Run subsyntax tool
    $ docker run -it styczynski/eniam:1.0 /root/subsyntax --help
    # Run lexicon printer
    $ docker run -it styczynski/eniam:1.0 /root/print_lexicon --help
    # Run DOM parser
    $ docker run -it styczynski/eniam:1.0 /root/domparser --help

Running with Python wrapper

You can install Python wrapper to get a nice wrapper around the docker container (this requires Python +3 and Docker installed):

    $ pip install eniam
    $ eniam-cli sub --help
    $ eniam-cli lex --help
    $ eniam-cli dom --help

Note: Before installing you may wish to add python /bin/ directory to the PATH variable. On MacOS for Python 3.7 that would be:

    $ export PATH="$PATH:/usr/local/Cellar/python/3.7.5/Frameworks/Python.framework/Versions/3.7/bin"

See setting up Python PATH