SubmissionNumber#=%=#2 FinalPaperTitle#=%=#Morphological Parsing for Media Lengua: When Accessibility Matters More Than State-of-the-Art ShortPaperTitle#=%=# NumberOfPages#=%=#9 CopyrightSigned#=%=#Olga Kriukova JobTitle#==# Organization#==# Abstract#==#While machine learning approaches dominate contemporary NLP research, a critical gap exists between published models and tools actually used by target communities (Gessler & von der Wense, 2024). This paper presents two morphological parsers for Media Lengua (ISO 639-3: mue), an endangered mixed language of Ecuador, demonstrating that a JavaScript rule-based system (98.6% accuracy) can outperform a CRF model (95.7% F1) while offering immediate community accessibility. Not all language structures permit straightforward rule-based parsing; however, when a language's morphology allows for this approach with competitive accuracy, we argue that it should be preferred for its practical advantages: immediate browser-based deployment, transparency, zero infrastructure requirements, and long-term maintainability. Our rule-based parser runs entirely in the browser, is freely available online, and can be adapted to other Quechuan languages. In contrast, while the CRF model performs well on benchmarks, it requires additional infrastructure to become accessible. Our comparison highlights the need to evaluate NLP tools not only on accuracy metrics but also on accessibility and real-world adoption, which is particularly crucial for endangered language communities where sustainable, community-accessible tools can support language documentation, education, and revitalization. Author{1}{Firstname}#=%=#Jesse Author{1}{Lastname}#=%=#Stewart Author{1}{Username}#=%=#dzesistuert Author{1}{Orcid}#=%=#https://orcid.org/0000-0001-8678-7884 Author{1}{Email}#=%=#stewart.jesse@usask.ca Author{1}{Affiliation}#=%=#University of Saskatchewan Author{2}{Firstname}#=%=#Olga Author{2}{Lastname}#=%=#Kriukova Author{2}{Username}#=%=#olk312 Author{2}{Orcid}#=%=#0000-0002-9375-421X Author{2}{Email}#=%=#olk312@usask.ca Author{2}{Affiliation}#=%=#University of Saskatchewan ========== èéáğö