Publication
PETra: A Multilingual Corpus of Pragmatic Explicitation in Translation
Doreen Osmelak; Koel Dutta Chowdhury; Uliana Sentsova; Cristina España-Bonet; Josef van Genabith
In: Stelios Piperidis; Núria Bel; Henk van den Heuvel; Nancy Ide; Simon Krek; Antonio Toral (Hrsg.). Proceedings of the Fifteenth Language Resources and Evaluation Conference (LREC 2026). International Conference on Language Resources and Evaluation (LREC-2026), Palma, Mallorca, Spain, Pages 8756-8766, European Language Resources Association (ELRA), 2026.
Abstract
Translators often enrich texts with background details that make implicit cultural meanings explicit for new audiences. This phenomenon, known as pragmatic explicitation, has been widely discussed in translation theory but rarely modeled computationally. We introduce PETra, the first multilingual corpus and detection framework for pragmatic explicitation. The corpus consists of 2,900 sentence pairs from TED-Multi and Europarl, covers twelve language pairs, and includes additions such as entity descriptions, measurement conversions, and translator remarks. We identify candidates through null alignments and refine them using active learning with human annotation. Our results show that entity and system-level (e.g., metric conversions) explicitations are most frequent, and that active learning improves classifier accuracy by 7-8 percentage points, achieving up to 0.88 accuracy and 0.82 F1 for the best transfer languages. PETra establishes pragmatic explicitation as a measurable, cross-linguistic phenomenon and takes a step towards building culturally aware machine translation.
