MAD: A Corpus of Multilingual Argumentative Deliberation
Proceedings of the Fifteenth Language Resources and Evaluation Conference (LREC 2026)
Abstract
We present a corpus of Multilingual Argumentative Deliberation (MAD), a manually annotated corpus of deliberative dialogues in English, German, Polish and Italian. Four groups each completed two variants of a ranking task, the NASA Survival Scenario; once in their native language and once in English. The corpus is annotated using Inference Anchoring Theory (IAT), a framework developed for analysing argument in dialogical settings, and widely used in argument mining. As an argument mining resource, MAD is distinct in offering equivalent instances of spontaneous argumentation across languages. In addition to use in argument mining, the annotation captures both argument relations and dialogue acts, enabling deeper analysis of argument and dialogue structure than typical of argument-only corpora. The design of the corpus enables studies of second-language effects in English-medium interaction, cross-linguistic argument comparisons for German, Polish and Italian, and speaker dialogue strategy consistency, amongst others. The primary annotated MAD corpus is freely available at https://corpora.aifdb.org/mad, while we additionally release the unannotated transcripts to facilitate repurposing of the material.