Proceedings of the Third Workshop on Resources and Representations for Under-Resourced Languages and Domains (RESOURCEFUL-2025)

Tartu : University of Tartu Library, 2025.

Editor-in-chief: Š. A. Holdt, N. Ilinykh, B. Scalvini, M. Bruton, I. N. Debess, C. M. Tudor

The third workshop on resources and representations for under-resourced languages and domains was held in Tallinn, Estonia, on March 2nd, 2025. The workshop was conducted in person but also provided an option for online participation. In alignment with the goals of the previous two workshops in 2020 and 2023, RESOURCEFUL-2025 explored the role of resource type and quality available to computational linguists, as well as the challenges and directions for constructing new resources in light of the latest trends in natural language processing, computational linguistics, and artificial intelligence. The workshop provided a forum for discussions between the two communities involved in building data-driven and annotation-driven resources. The call for papers for RESOURCEFUL-2025 requested work on the following topics: • The types of linguistic knowledge that should be captured by models across different contexts and tasks • Practical methods for sampling and extracting knowledge • The relevance of traditional NLP resources for use in data-driven approaches • The use of data-driven approaches to enhance expert-driven annotation processes • Current challenges faced in expert-based annotation • Crowdsourcing and citizen science initiatives to build and enrich linguistic resources • Methods for evaluating and mitigating unwanted biases in linguistic models and data • Creating anonymized and pseudonymized datasets and models • Evaluating the role of modern LLMs in the creation of new linguistic resources

Chapters

The application of corpus-based language distance measurement to the diatopic variation study (on the material of the Old Novgorodian birchbark letters)

Afanasev I., Lyashevskaya O., , in: Proceedings of the Third Workshop on Resources and Representations for Under-Resourced Languages and Domains (RESOURCEFUL-2025).: Tartu: University of Tartu Library, 2025. P. 153–164.

The paper presents a computer-assisted exploration of a set of texts, where qualitative analysis complements the linguistically-aware vector-based language distance measurements, interpreting them through close reading and thus proving or disproving their conclusions. It proposes using a method designed for small raw corpora to explore the individual, chronological, and gender-based differences within an extinct single ...

Added: July 17, 2025

Keywords: NLP, NLP evaluation, data-driven approach