WIQA: A dataset for "What if..." reasoning over procedural text

09/10/2019
by   Niket Tandon, et al.
0

We introduce WIQA, the first large-scale dataset of "What if..." questions over procedural text. WIQA contains three parts: a collection of paragraphs each describing a process, e.g., beach erosion; a set of crowdsourced influence graphs for each paragraph, describing how one change affects another; and a large (40k) collection of "What if...?" multiple-choice questions derived from the graphs. For example, given a paragraph about beach erosion, would stormy weather result in more or less erosion (or have no effect)? The task is to answer the questions, given their associated paragraph. WIQA contains three kinds of questions: perturbations to steps mentioned in the paragraph; external (out-of-paragraph) perturbations requiring commonsense knowledge; and irrelevant (no effect) perturbations. We find that state-of-the-art models achieve 73.8 the challenges, in particular tracking chains of influences, and present the dataset as an open challenge to the community.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
03/21/2022

Relevant CommonSense Subgraphs for "What if..." Procedural Reasoning

We study the challenge of learning causal reasoning over procedural text...
research
06/11/2021

TellMeWhy: A Dataset for Answering Why-Questions in Narratives

Answering questions about why characters perform certain actions is cent...
research
03/14/2018

MCScript: A Novel Dataset for Assessing Machine Comprehension Using Script Knowledge

We introduce a large dataset of narrative texts and questions about thes...
research
09/16/2022

Possible Stories: Evaluating Situated Commonsense Reasoning under Multiple Possible Scenarios

The possible consequences for the same context may vary depending on the...
research
09/08/2019

Large Scale Question Answering using Tourism Data

Real world question answering can be significantly more complex than wha...
research
09/08/2019

QuaRTz: An Open-Domain Dataset of Qualitative Relationship Questions

We introduce the first open-domain dataset, called QuaRTz, for reasoning...
research
05/16/2019

Dynamically Fused Graph Network for Multi-hop Reasoning

Text-based question answering (TBQA) has been studied extensively in rec...

Please sign up or login with your details

Forgot password? Click here to reset