2019 ACL ACL 2019

Annotating Information Structure in Italian: Characteristics and Cross-Linguistic Applicability of a QUD-Based Approach

Abstract

AbstractWe present a discourse annotation study, in which an annotation method based on Questions under Discussion (QuD) is applied to Italian data. The results of our inter-annotator agreement analysis show that the QUD-based approach, originally spelled out for English and German, can successfully be transferred cross-linguistically, supporting good agreement for the annotation of central information structure notions such as focus and non-at-issueness. Our annotation and interannotator agreement study on Italian authentic data confirms the cross-linguistic applicability of the QuD-based approach.

🌉 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, Speech & Audio