2026 EACL EACL 2026

DELTA: A Toolkit for Measuring Linguistic Diversity in Dependency-Parsed Corpora

Abstract

AbstractDespite growing interest in measuring linguistic diversity on the one hand and the increasing availability of cross-linguistically comparable parsed corpora on the other, tools for systematically measuring the diversity of specific linguistic phenomena on such data remain limited. To address this gap, we present DELTA, an open-source framework that integrates dependency tree querying with diversity computation, enabling systematic measurement across multiple linguistic levels (e.g., lexis, morphology, syntax) and multiple diversity dimensions (variety, balance, disparity). The pipeline processes CoNLL-U formatted corpora through configurable workflows, treating the format as a general-purpose tabular structure independent of specific annotation conventions. We validate DELTA on Parallel Universal Dependencies multilingual dataset, demonstrating its capacity for corpus profiling and cross-corpus diversity comparison.

🌉 Interdisciplinary Bridge — Interdisciplinary and Natural Language Processing
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio