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TabFact

Introduced in TabFact: A Large-scale Dataset for Table-based Fact Verification2019

About this Dataset

TabFact is a large-scale dataset which consists of 117,854 manually annotated statements with regard to 16,573 Wikipedia tables, their relations are classified as ENTAILED and REFUTED. TabFact is the first dataset to evaluate language inference on structured data, which involves mixed reasoning skills in both symbolic and linguistic aspects.

Source: GitHub

Source: TabFact: A Large-scale Dataset for Table-based Fact Verification

Dataset Variants

TabFact

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TabFact: A Large-scale Dataset for Table-based Fact Verification

A large-scale dataset with 16k Wikipedia tables as the evidence for 118k human-annotated natural language statements, which are labeled as either ENTAILED or REFUTED is constructed and two different models are designed: Table-BERT and Latent Program Algorithm (LPA).

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Natural Language Inference Table-based Fact Verification

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