SOTAVerified

Detecting Temporal Ambiguity in Questions

2024-09-25Code Available0· sign in to hype

Bhawna Piryani, Abdelrahman Abdallah, Jamshid Mozafari, Adam Jatowt

Code Available — Be the first to reproduce this paper.

Reproduce

Code

Abstract

Detecting and answering ambiguous questions has been a challenging task in open-domain question answering. Ambiguous questions have different answers depending on their interpretation and can take diverse forms. Temporally ambiguous questions are one of the most common types of such questions. In this paper, we introduce TEMPAMBIQA, a manually annotated temporally ambiguous QA dataset consisting of 8,162 open-domain questions derived from existing datasets. Our annotations focus on capturing temporal ambiguity to study the task of detecting temporally ambiguous questions. We propose a novel approach by using diverse search strategies based on disambiguated versions of the questions. We also introduce and test non-search, competitive baselines for detecting temporal ambiguity using zero-shot and few-shot approaches.

Tasks

Reproductions