Opacity, Obscurity, and the Geometry of Question-Asking

09/21/2018
by   Christina Boyce-Jacino, et al.
0

Asking questions is a pervasive human activity, but little is understood about what makes them difficult to answer. An analysis of a pair of large databases, of New York Times crosswords and questions from the quiz-show Jeopardy, establishes two orthogonal dimensions of question difficulty: obscurity (the rarity of the answer) and opacity (the indirectness of question cues, operationalized with word2vec). The importance of opacity, and the role of synergistic information in resolving it, suggests that accounts of difficulty in terms of prior expectations captures only a part of the question-asking process. A further regression analysis shows the presence of additional dimensions to question-asking: question complexity, the answer's local network density, cue intersection, and the presence of signal words. Our work shows how question-askers can help their interlocutors by using contextual cues, or, conversely, how a particular kind of unfamiliarity with the domain in question can make it harder for individuals to learn from others. Taken together, these results suggest how Bayesian models of question difficulty can be supplemented by process models and accounts of the heuristics individuals use to navigate conceptual spaces.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
07/10/2018

Difficulty Controllable Question Generation for Reading Comprehension

Question generation aims to generate natural language questions from a r...
research
05/25/2021

Guiding the Growth: Difficulty-Controllable Question Generation through Step-by-Step Rewriting

This paper explores the task of Difficulty-Controllable Question Generat...
research
05/24/2023

Selectively Answering Ambiguous Questions

Trustworthy language models should abstain from answering questions when...
research
07/17/2022

Can large language models reason about medical questions?

Although large language models (LLMs) often produce impressive outputs, ...
research
04/05/2016

Modeling Relational Information in Question-Answer Pairs with Convolutional Neural Networks

In this paper, we propose convolutional neural networks for learning an ...
research
04/05/2021

What's the best place for an AI conference, Vancouver or ______: Why completing comparative questions is difficult

Although large neural language models (LMs) like BERT can be finetuned t...
research
12/31/2019

Essential Sentences for Navigating Stack Overflow Answers

Stack Overflow (SO) has become an essential resource for software develo...

Please sign up or login with your details

Forgot password? Click here to reset