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@espositopasquale espositopasquale released this 21 Jul 07:14
1.0.0
5c88fb8

Release Notes — Appìl 1.0.0

Overview

Appìl is an interactive, NLP-powered platform for lexical and linguistic competence improvement, developed as part of the accompanying doctoral thesis. This release packages the full three-tier system — Spring Boot backend, Flask NLP microservice, and MySQL database — into a reproducible, containerized deployment, together with complete project documentation.

Highlights

  • Word Sense Disambiguation via Lesk-based algorithms over WordNet
  • Named Entity Recognition via spaCy (en_core_web_sm)
  • Interactive semantic graphs (synonyms, antonyms, meronyms, holonyms) rendered with D3.js
  • Lexical progress analytics backed by MySQL / Spring Data JPA
  • CEFR-aligned personalization of flashcards and exercises
  • One-command Docker Compose deployment

What's Included

Application

  • Spring Boot 3 (Java 17) web application, packaged as a WAR, in java-app/
  • Flask/Gunicorn NLP microservice exposing /disambiguate and /ner, in python-service/
  • MySQL 8.0 schema with automatic initialization
  • docker-compose.yml for orchestrated multi-container deployment
  • Interactive setup.sh script for manual, non-Docker configuration

Documentation

  • README.md: project overview, architecture with request-flow walkthrough, project structure, technology stack, installation and development instructions, full API reference for the NLP endpoints, and the research background grounding the system in SLA theory
  • ATTRIBUTIONS.md: a complete, license-annotated inventory of every open-source library and open knowledge resource used in the project — including WordNet, Wikipedia, Wiktionary, NLTK, PyWSD, spaCy, Three.js, D3.js, Spring Boot, Flask, MySQL, and Docker — with a license summary table
  • LICENSE-MIT: license covering the Appìl source code
  • LICENSE-CC: license covering CC BY-SA–derived content (e.g., Wikipedia/Wiktionary-sourced material)

Known Limitations

  • The project was developed and evaluated by a single researcher; contributor tooling (CI, issue templates, contribution guidelines) is not yet in place.
  • No automated test suite is currently included in this release.
  • Screenshots/GIFs of the UI are not yet included in the README.

Acknowledgements

This release is built on the open-source and open-knowledge ecosystem documented in ATTRIBUTIONS.md, including WordNet, NLTK, PyWSD, spaCy, Three.js, D3.js, Spring Boot, Flask, MySQL, Docker, and Wikipedia/Wiktionary.

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