Papers › From Dataset Recycling to Multi-Property Extraction and Beyond

From Dataset Recycling to Multi-Property Extraction and Beyond

6 Nov 2020CONLL 2020arXiv:2011.03228archive 2025-07-28

Tomasz Dwojak, Michał Pietruszka, Łukasz Borchmann, Jakub Chłędowski, Filip Graliński

This paper investigates various Transformer architectures on the WikiReading Information Extraction and Machine Reading Comprehension dataset. The proposed dual-source model outperforms the current state-of-the-art by a large margin. Next, we introduce WikiReading Recycled-a newly developed public dataset and the task of multiple property extraction. It uses the same data as WikiReading but does not inherit its predecessor's identified disadvantages. In addition, we provide a human-annotated test set with diagnostic subsets for a detailed analysis of model performance.

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Tasks

DiagnosticMachine Reading ComprehensionReading Comprehension

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WikiReading Recycled

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Methods

Absolute Position EncodingsAdamAttentionBPEDense ConnectionsDropoutLabel SmoothingLayer NormalizationLinear LayerMulti-Head AttentionPosition-Wise Feed-Forward LayerResidual ConnectionSoftmaxTransformer

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