QuaRTz: An Open-Domain Dataset of Qualitative Relationship Questions

September 08, 2019 ยท Declared Dead ยท ๐Ÿ› Conference on Empirical Methods in Natural Language Processing

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Authors Oyvind Tafjord, Matt Gardner, Kevin Lin, Peter Clark arXiv ID 1909.03553 Category cs.CL: Computation & Language Cross-listed cs.AI Citations 115 Venue Conference on Empirical Methods in Natural Language Processing Last Checked 4 months ago
Abstract
We introduce the first open-domain dataset, called QuaRTz, for reasoning about textual qualitative relationships. QuaRTz contains general qualitative statements, e.g., "A sunscreen with a higher SPF protects the skin longer.", twinned with 3864 crowdsourced situated questions, e.g., "Billy is wearing sunscreen with a lower SPF than Lucy. Who will be best protected from the sun?", plus annotations of the properties being compared. Unlike previous datasets, the general knowledge is textual and not tied to a fixed set of relationships, and tests a system's ability to comprehend and apply textual qualitative knowledge in a novel setting. We find state-of-the-art results are substantially (20%) below human performance, presenting an open challenge to the NLP community.
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