@inproceedings{christian-2026-interactive,
    title = "An Interactive System for Generating Revisable Grammar Lessons for Extremely Low-Resource Languages Without Expert Annotation",
    author = "Christian, Sebastien",
    editor = "Agyapong, Godfred  and
      Moeller, Sarah  and
      Arppe, Antti  and
      Marashian, Ali  and
      Rosenblum, Daisy",
    booktitle = "Proceedings of the Ninth Workshop on the Use of Computational Methods in the Study of Endangered Languages ({C}omput{EL}-9)",
    month = jul,
    year = "2026",
    address = "San Diego, California, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.computel-1.4/",
    pages = "26--36",
    ISBN = "979-8-89176-422-4",
    abstract = "Endangered-language teaching often faces two practical bottlenecks: the scarcity of experts able to produce pedagogical grammars, and the dependence of most approaches on expert linguistic annotation. We present a human-in-the-loop system for extremely low-resource languages that addresses both constraints by combining lightweight concept-based annotation, typological inference, structured sentence-pair augmentation, document retrieval, and constrained language model generation. Rather than aiming to produce definitive grammatical descriptions, the system generates revisable grammar lesson drafts grounded in heterogeneous evidence, including elicited sentence pairs, free translation pairs, and descriptive documents. The interface is designed so that speakers, teachers, and other language practitioners without formal linguistic training can contribute usable data, inspect intermediate inferences, control source selection and generate draft grammar lessons. We describe the architecture, user workflows, and initial deployment experience in real-world revitalization settings. The contribution of the paper is an implemented workflow for early pedagogical draft generation under extreme data scarcity, not a controlled evaluation of pedagogical effectiveness."
}