MuLMS-AZ (Multi-Layer Materials Science - Argumentative Zoning)
Introduced by Schrader et al. in MuLMS-AZ: An Argumentative Zoning Dataset for the Materials Science Domain
The Multi-Layer Materials Science Argumentative Zoning (MuLMS-AZ) corpus consists of 50 documents (licensed CC BY) from the materials science domain, spanning across the following 7 sub-areas: "Electrolysis", "Graphene", "Polymer Electrolyte Fuel Cell (PEMFC)", "Solid Oxide Fuel Cell (SOFC)", "Polymers", "Semiconductors" and "Steel". There are annotations on sentence-level and token-level for several NLP tasks, including Argumentative Zoning (AZ). Every sentence in the dataset is labelled with one or multiple argumentative zones. The dataset can be used to train classifiers and text mining systems on argumentative zoning in the materials science domain.
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