This paper presents a brief description of some morphosyntactic features of Ancash Quechua, the majority variety of the Central Quechua language family (QI), for the purpose of building a corpus annotated according to the Universal Dependencies (UD) schema. The creation of such a corpus has two objectives: for Quechua linguistics, it opens up the possibility of more systematic linguistic studies and comparisons with other languages. It also enables the development of a syntactic parser, which would be the first NLP tool for a Quechua language of this family. For the UD project, adding Quechua, an agglutinative language with a rich morphology, makes it possible to point out some possible shortcomings of the universal annotation schema, and to fuel the discussion to adapt this schema to the specific features of the languages with a similar typology. The first step towards this work was first to gather and digitise the available linguistic resources, thus creating the first bilingual and sentence-aligned digital corpus in Ancash Quechua and Spanish. After identifying some linguistic features not fully described in the UD schema, we proposed annotation solutions, and built an initial corpus of around twenty sentences, which we are making freely available.

The Quechua linguistic family has a limited number of NLP resources, most of them being dedicated to Southern Quechua, whereas the varieties of Central Quechua have, to the best of our knowledge, no specific resources (software, lexicon or corpus). Our work addresses this issue by producing two resources for the Ancash Quechua: a full digital version of a dictionary, and an OCR model adapted to the considered variety. In this paper, we describe the steps towards this goal: we first measure performances of existing models for the task of digitising a Quechua dictionary, then adapt a model for the Ancash variety, and finally create a reliable resource for NLP in XML-TEI format. We hope that this work will be a basis for initiating NLP projects for Central Quechua, and that it will encourage digitisation initiatives for under-resourced languages.