Vivek Gupta
KNOWLEDGE_INFOTABS
TabPert
Understanding ubiquitous semi-structured tabulated data requires not only comprehending the meaning of text fragments, but also implicit relationships between them. We argue that such data can prove as a testing ground for understanding how we reason about information. To study this, we introduce a new dataset called INFOTABS, comprising of human-written textual hypotheses based on premises that are tables extracted from Wikipedia info-boxes. Our analysis shows that the semi-structured, multi-domain and het
tldr: INFOTABS is a Semi-structured inference dataset with wikipedia Infobox tables as premise and human written statements as hypothesis. Procedure We use Amazon Mechanical Turk ( mturk ) for data collection and validation. Annotators were presented with a tabular premise (infobox tables) and instructed to write three self-contained grammatical sentences based on the tables: one of which is true given the table, one which is false, and one which may or may not be true. We provide detailed instructions with
Below is an inference example from the INFOTABS dataset. On the right is a premise which is a table extracted from wikipedia infobox. On the left are hypotheses written by human annotators. Here, colors 'green'
Vivek Gupta
KNOWLEDGE_INFOTABS
TabPert