A Wrong Answer or a Wrong Question? An Intricate Relationship between Question Reformulation and Answer Selection in Conversational Question Answering

10/13/2020
by   Svitlana Vakulenko, et al.
1

The dependency between an adequate question formulation and correct answer selection is a very intriguing but still underexplored area. In this paper, we show that question rewriting (QR) of the conversational context allows to shed more light on this phenomenon and also use it to evaluate robustness of different answer selection approaches. We introduce a simple framework that enables an automated analysis of the conversational question answering (QA) performance using question rewrites, and present the results of this analysis on the TREC CAsT and QuAC (CANARD) datasets. Our experiments uncover sensitivity to question formulation of the popular state-of-the-art models for reading comprehension and passage ranking. Our results demonstrate that the reading comprehension model is insensitive to question formulation, while the passage ranking changes dramatically with a little variation in the input question. The benefit of QR is that it allows us to pinpoint and group such cases automatically. We show how to use this methodology to verify whether QA models are really learning the task or just finding shortcuts in the dataset, and better understand the frequent types of error they make.

READ FULL TEXT
03/11/2021

Conversational Answer Generation and Factuality for Reading Comprehension Question-Answering

Question answering (QA) is an important use case on voice assistants. A ...
11/14/2017

Evidence Aggregation for Answer Re-Ranking in Open-Domain Question Answering

A popular recent approach to answering open-domain questions is to first...
10/09/2021

A Framework for Rationale Extraction for Deep QA models

As neural-network-based QA models become deeper and more complex, there ...
11/05/2020

Context-Aware Answer Extraction in Question Answering

Extractive QA models have shown very promising performance in predicting...
04/20/2018

Right Answer for the Wrong Reason: Discovery and Mitigation

Exposing the weaknesses of neural models is crucial for improving their ...
06/07/2019

RankQA: Neural Question Answering with Answer Re-Ranking

The conventional paradigm in neural question answering (QA) for narrativ...
04/01/2022

Multifaceted Improvements for Conversational Open-Domain Question Answering

Open-domain question answering (OpenQA) is an important branch of textua...