italian-ats-evaluator 2.0.8

Italian ATS Evaluator

italian-ats-evalautor

This is an open source project to evaluate the performance of an italian ATS (Automatic Text Simplifier) on a set of texts.

You can analyze a single text extracting the following features:

• Overall:
  • Number of tokens
  • Number of tokens (including punctuation)
  • Number of characters
  • Number of characters (including punctuation)
  • Number of words
  • Number of syllables
  • Number of unique lemmas
  • Number of sentences
• Readability:
  • Type-Token Ratio (TTR)
  • Gulpease Index
  • Flesch-Vacca Index
  • Lexical Density
• Part of Speech (POS) distribution
• Verbs distribution
  • Active Verbs
  • Passive Verbs
• Italian Basic Vocabulary (NVdB) from Il Nuovo vocabolario di base della lingua italiana, Tullio De Mauro
  • All
  • FO (Fundamentals)
  • AU (High Usage)
  • AD (High Availability)
• Expression:
  • Difficult connectives
  • Latinisms

You can also compare two texts and get the following metrics:

• Semantic:
  • Semantic Similarity
• Character diff:
  • Edit Distance
• Token diff:
  • Amount of tokens added
  • Amount of tokens removed
  • Amount of VdB tokens removed
  • Amount of VdB tokens added

Installation

pip install italian-ats-evaluator

Usage

from italian_ats_evaluator import TextAnalyzer

result = TextAnalyzer(
  text="Il gatto mangia il topo",
  spacy_model_name="it_core_news_lg"
)

from italian_ats_evaluator import SimplificationAnalyzer

result =  SimplificationAnalyzer(
  reference_text="Il felino mangia il roditore",
  simplified_text="Il gatto mangia il topo",
  spacy_model_name="it_core_news_lg",
  sentence_transformers_model_name="intfloat/multilingual-e5-base"
)

Development

Create a virtual environment

python3 -m venv venv
source venv/bin/activate

Install the package in editable mode

pip install -e .

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Acknowledgements

This contribution is a result of the research conducted within the framework of the PRIN 2020 (Progetti di Rilevante Interesse Nazionale) “VerbACxSS: on analytic verbs, complexity, synthetic verbs, and simplification. For accessibility” (Prot. 2020BJKB9M), funded by the Italian Ministero dell’Università e della Ricerca.

License

MIT