Journal Article

Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies

Berant, Jonathan, Roth, Dan, Geva, Mor, Segal, Elad, Khot, Tushar, Khashabi, Daniel

2021

Overview

A key limitation in current datasets for is that the required steps for answering the question are mentioned in it . In this work, we introduce S QA, a question answering (QA) benchmark where the required reasoning steps are in the question, and should be inferred using a . A fundamental challenge in this setup is how to elicit such creative questions from crowdsourcing workers, while covering a broad range of potential strategies. We propose a data collection procedure that combines term-based priming to inspire annotators, careful control over the annotator population, and adversarial filtering for eliminating reasoning shortcuts. Moreover, we annotate each question with (1) a decomposition into reasoning steps for answering it, and (2) Wikipedia paragraphs that contain the answers to each step. Overall, S QA includes 2,780 examples, each consisting of a strategy question, its decomposition, and evidence paragraphs. Analysis shows that questions in S QA are short, topic-diverse, and cover a wide range of strategies. Empirically, we show that humans perform well (87%) on this task, while our best baseline reaches an accuracy of ∼ 66 .

• Publisher: MIT Press,MIT Press Journals, The,The MIT Press
• Subject: Answers / Benchmarks / Computational linguistics / Creativity / Crowdsourcing / Data collection / Decomposition / Helium / Information sources / Internet / Linguistics / Paragraphs / Priming / Question answer sequences / Questions / Reasoning / Strategies