Delexicalised Multilingual Discourse Segmentation for DISRPT 2021 and Tense, Mood, Voice and Modality Tagging for 11 Languages

Abstract

This paper describes our participating system for the Shared Task on Discourse Segmentation and Connective Identification across Formalisms and Languages. Key features of the presented approach are the formulation as a clause-level classification task, a language-independent feature inventory based on Universal Dependencies grammar, and composite-verb-form analysis. The achieved F1 is 92% for German and English and lower for other languages. The paper also presents a clause-level tagger for grammatical tense, aspect, mood, voice and modality in 11 languages.