DexFlex Documentation

DexFlex is a Python package for Romanian language processing.
It leverages dexonline to extract dictionary data, applies rule-based methods, and integrates spaCy with the Romanian model ro_core_news_lg.
The library provides functionality such as inflection handling, synonym suggestions, and transformations between tenses and voices.

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Installation

DexFlex is available on PyPI:

pip install dexflex

• On the first run, a setup script will be executed to fetch and prepare the dictionary data required by DexFlex. This process may take a few minutes depending on your internet connection.

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Features

🔹 Inflection Handling

For a given target word, extract all inflectional forms.

🔹 Tense Transformation

Automated switching between past perfect and past simple.

🔹 Synonym Suggestions

Context-aware synonym generation.

🔹 Voice Transformation

Convert active → passive voice and passive → active voice.

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Synonym Suggestion Process

Synonym generation is performed in four steps:

1. Identify the current contextual meaning of the word
2. Select synonyms that match the sentence’s meaning
3. Inflect synonyms to match the contextual grammatical form
4. Heuristically sort and return synonyms

Sorting Criteria

• Length of the word
• Dictionary ordering
• Approximate syllable count
• Similarity with context embeddings
• Frequency

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Usage

Import

pip install dexflex

from dexflex.prototype import *
import spacy

nlp = spacy.load("ro_core_news_lg")

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Example 1: Inflection Handling

data_aif = [
    ("ocol", 0),
    ("Rece, crudă, geloasă pe frumusețea și șarmul Cenușăresei,", 2),
    ("Ea era hotărâtă să susțină interesele propriilor sale fiice.", 0),
    ("Castelul a ajuns o ruină.", 0),
]

for sample in data_aif:
    doc = nlp(sample[0])
    all_forms_for_word = get_all_forms(doc[sample[1]])

    print(f"For target-word: {doc[sample[1]]} there are all the inflected forms:")
    for form in all_forms_for_word:
        print(form)
    print("\n\n")

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Example 2: Synonym Suggestions

samples = [
    ("Am observat eroarea la timp.", 2),
    ("Ea a învățat să cânte la pian.", 4),
    ("Am observat eroarea la timp.", 1),
    ("Ei au reparat mașina stricată.", -2),
    ("Tu ai scris o poezie frumoasă.", -2),
    ("Ea s-a gătit pentru o cină delicioasă.", 3),
    ("El a uitat să aducă documentele.", -2),
    ("Ea a primit un cadou de ziua ei.", 4),
    ("Tu ai vorbit cu profesorul?", -2),
    ("Ei au construit un parc nou.", 2),
    ("El a plecat la camera lui.", -3)
]

for sample in samples:
    doc = nlp(sample[0])
    syn_list = [syn[0] for syn in doc[sample[1]]._.get_syns()]
    print(f"Synonyms for: {doc[sample[1]]} are {syn_list}")

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Additional Notes

• DexFlex uses dexonline data, transformed into JSON files for efficient lookups.
• Example contexts are stored as embeddings in .feather format for better memory handling.
• A working demo is provided in demo.ipynb.

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Resources

• 📚 DexOnline reference: github.com/dexonline/dexonline
• 📦 PyPI package: pypi.org/project/dexflex
• 🔎 SpaCy Romanian model: ro_core_news_lg

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