Evaluating Co-reference Chains based Conversation History in Conversational Question Answering



Mandya, AA, Bollegala, D ORCID: 0000-0003-4476-7003 and Coenen, FP ORCID: 0000-0003-1026-6649
(2020) Evaluating Co-reference Chains based Conversation History in Conversational Question Answering. In: 16th International Conference of the Pacific Association for Computational Linguistics, PACLING 2019, 2019-10-11 - 2019-10-13, Hanoi, Vietnam.

[img] Text
pacling_2019_Angrosh_camera_ready.pdf - Author Accepted Manuscript

Download (373kB) | Preview

Abstract

This paper examines the effect of using co-reference chains based conversational history against the use of entire conversation history for conversational question answering (CoQA) task. The QANet model is modified to include conversational history and NeuralCoref is used to obtain co-reference chains based conversation history. The results of the study indicates that in spite of the availability of a large proportion of co-reference links in CoQA, the abstract nature of questions in CoQA renders it difficult to obtain correct mapping of co-reference related conversation history, and thus results in lower performance compared to systems that use entire conversation history. The effect of co-reference resolution examined on various domains and different conversation length, shows that co-reference resolution across questions is helpful for certain domains and medium-length conversations.

Item Type: Conference or Workshop Item (Unspecified)
Uncontrolled Keywords: Co-referenced based conversation history, Conversational question answering, QANet
Depositing User: Symplectic Admin
Date Deposited: 25 Aug 2020 07:33
Last Modified: 18 Jan 2023 23:36
DOI: 10.1007/978-981-15-6168-9_24
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3098685