Turoyo morphological analyzer

This is a rule-based morphological analyzer for Ṭuroyo (tru, Afro-Asiatic > Central Neo-Aramaic). It is based on a formalized description of Turoyo morphology and uses uniparser-morph for parsing. It performs full morphological analysis of Turoyo words (lemmatization, POS tagging, grammatical tagging). The text to be analyzed should be written in a version of Latin Turoyo alphabet which is somewhat closer to IPA: it uses ʔ instead of ', ʕ instead of c, ə insteadt of ë etc.

How to use

Python package

The analyzer is available as a Python package. If you want to analyze Turoyo texts in Python, install the module:

pip3 install uniparser-turoyo

Import the module and create an instance of TuroyoAnalyzer class. Set mode='strict' if you are going to process text in standard Latin Turoyo alphabet, or mode='nodiacritics' if you expect some words to lack the diacritics (e.g. t instead of ṭ). After that, you can either parse tokens or lists of tokens with analyze_words(), or parse a frequency list with analyze_wordlist(). Here is a simple example:

from uniparser_turoyo import TuroyoAnalyzer
a = TuroyoAnalyzer(mode='strict')

analyses = a.analyze_words('koroḥamnux')
# The parser is initialized before first use, so expect
# some delay here (usually several seconds)

# You will get a list of Wordform objects
# The analysis attributes are stored in its properties
# as string values, e.g.:
for ana in analyses:
        print(ana.wf, ana.lemma, ana.gramm)

# You can also pass lists (even nested lists) and specify
# output format ('xml', 'json' or 'conll')
# If you pass a list, you will get a list of analyses
# with the same structure
analyses = a.analyze_words([['koroḥamnux'], ['ʕəbarwo', 'lab', 'bote', '.']],
	                       format='xml')
analyses = a.analyze_words([['koroḥamnux'], ['ʕəbarwo', 'lab', 'bote', '.']],
	                       format='conll')
analyses = a.analyze_words(['koroḥamnux', [['laḥmawo'], ['ʕəbarwo', 'lab', 'bote', '.']]],
	                       format='json')

Refer to the uniparser-morph documentation for the full list of options.

If you want to quickly check an analysis for one particular word, you can also use the command-line interface. Here is an example for the word koroḥamnux:

python3 -m uniparser_turoyo koroḥamnux

Word lists

Alternatively, you can use a preprocessed word list. The wordlists directory contains a list of words from a 600-thousand-word Ṭuroyo corpus (wordlist.csv) with 53,000 unique tokens, list of analyzed tokens (wordlist_analyzed.txt; each line contains all possible analyses for one word in an XML format), and list of tokens the parser could not analyze (wordlist_unanalyzed.txt). The recall of the analyzer on the corpus texts is about 90%. (This number is somewhat low due to orthographic variability in the texts.)

Description format

The description is carried out in the uniparser-morph format and involves a description of the inflection (paradigms/paradigms_XXX.txt) and a grammatical dictionary (lexemes/lexemes-XXX.txt files). The dictionary contains descriptions of individual lexemes, each of which is accompanied by information about its stem, its part-of-speech tag and some other grammatical information, its consonant root, its inflectional type (paradigm), and English and/or German translations. See more about the format in the uniparser-morph documentation.