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Supplementary data for the EACL 2023 Paper: "Made of Steel? Learning Plausible Materials for Components in the Vehicle Repair Domain"

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Supplementary Data

This is the supplementary data for the following paper:

"Made of Steel? Learning Plausible Materials for Components in the Vehicle Repair Domain" by Annerose Eichel, Helena Schlipf and Sabine Schulte im Walde to be published at EACL 2023.

The data consists of the following files:

data/sampled_components.csv: The 100 sampled full components.
data/sampled_components_with_heads.csv: The 100 sampled full and head components used for query template analysis (cf. §4.1) and evaluation (cf. §6).

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Supplementary data for the EACL 2023 Paper: "Made of Steel? Learning Plausible Materials for Components in the Vehicle Repair Domain"

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