African Wordnet Zulu adjectives tool

Introduction

The tool presented here is based on the Zulu Grammatical Framework resource grammar and seeks to extend the usage of adjectives in the Zulu African Wordnet as described in Marais, L & Pretorius, L. "Extending the Usage of Adjectives in the Zulu AfWN". Global Wordnet Conference 2023 (to appear). For more information, see GWC2023.

Prelimininaries

Install the pgf Python package.

$ pip3 install pgf

Running the tool

Run the following to see the top-level usage instructions.

$ python3 afwn_adjectives.py -h

usage: afwn_adjectives.py [-h] {query,generate,analyze} ...

positional arguments:
  {query,generate,analyze}
                        sub-command help
    query               check support for an English adjective
    generate            get correct Zulu qualificative constructions (enclose multiword adjectives in quotes, use ? as wild card)
    analyze             get analysis of a Zulu qualificative

optional arguments:
  -h, --help            show this help message and exit

Query English

To check for support for English adjectives, use query.

$ python3 afwn_adjectives.py query -h

usage: afwn_adjectives.py query [-h] adjective

positional arguments:
  adjective   adjective or part of an adjective (English)

optional arguments:
  -h, --help  show this help message and exit

For example:

$ python3 afwn_adjectives.py query wrong
wrong
wrongful

Generate Zulu

To see the Zulu form(s) of English adjectives, use generate.

$ python3 afwn_adjectives.py generate -h

usage: afwn_adjectives.py generate [-h] [--csv]
                         {Pres,Past,Fut,RemPast,RemFut,?} {Pos,Neg,?} {1,1a,2,2a,3,4,5,6,7,8,9,10,11,14,15,17,?} {Attr,Pred,?} adjective

positional arguments:
  {Pres,Past,Fut,RemPast,RemFut,?}
  {Pos,Neg,?}
  {1,1a,2,2a,3,4,5,6,7,8,9,10,11,14,15,17,?}
  {Attr,Pred,?}
  adjective

optional arguments:
  -h, --help            show this help message and exit
  --csv                 print output in csv format

Some examples to try:

$ python3 afwn_adjectives.py generate Pres Pos 1 Pred happy
$ python3 afwn_adjectives.py generate Pres Pos 5 Attr unfortunate
$ python3 afwn_adjectives.py generate ? Neg 9 Pred accessible
$ python3 afwn_adjectives.py generate Past ? 9 Pred heated
$ python3 afwn_adjectives.py generate Pres Pos 9 ? improved
$ python3 afwn_adjectives.py generate Past Neg 7 Attr "three legged"

Analyze Zulu

To analyze Zulu qualificatives, use analyze.

usage: afwn_adjectives.py analyze [-h] qualificative

positional arguments:
qualificative  Zulu qualificative (multi-token constructions should be enclosed in quotations)

optional arguments:
-h, --help     show this help message and exit

Some examples to try:

$ python3 afwn_adjectives.py analyze unomsindo
$ python3 afwn_adjectives.py analyze uyangeneka
$ python3 afwn_adjectives.py analyze ongekenayo
$ python3 afwn_adjectives.py analyze "esinemilenze emithathu"

Compiling the grammars

The latest code of the ZRG can be obtained as part of the official GF RGL repository. In addition, the rg folder in this repository contains extension modules with which the version of the ZRG used in this project can be compiled. Install the latest version of GF and clone the gf-rgl code from Github. Let GF_RGL point to the gf-rgl folder on your machine and set the GF_LIB_PATH variable as follows

export GF_LIB_PATH=$GF_LIB_PATH:$GF_RGL/src/*:$GF_RGL/src/zulu/*

Then compile ZWNAdjectives.pgf with

gf --make ZWNAdjectivesZul.gf

Or compile the ZRG directly with

cd rg/
gf --make ZWNLangZul.gf

Other resources

We have included map.csv, which captures the VP tree structures associated with the ZWN written forms along with other relevant information.

We have also included analysis.selection, which is the output of the process followed to evaluate this tool as having 96% accuracy. The ZulMorph morphological analyser was used to validate generated tokens, along with some manual evaluation where morphological analysis failed.