Query graph generation for answering multi-hop complex questions from knowledge bases
Previous work on answering complex questions from knowledge bases usually separately addresses two types of complexity: questions with constraints and questions with multiple hops of relations. In this paper, we handle both types of complexity at the same time. Motivated by the observation that earl...
Saved in:
Main Authors: | , |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2020
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/5271 https://ink.library.smu.edu.sg/context/sis_research/article/6274/viewcontent/7._Query_Graph_Generation_for_Answering_Multi_hop_Complex_Questions__ACL2020_.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
id |
sg-smu-ink.sis_research-6274 |
---|---|
record_format |
dspace |
spelling |
sg-smu-ink.sis_research-62742020-08-14T04:01:12Z Query graph generation for answering multi-hop complex questions from knowledge bases LAN, Yunshi Jing JIANG, Previous work on answering complex questions from knowledge bases usually separately addresses two types of complexity: questions with constraints and questions with multiple hops of relations. In this paper, we handle both types of complexity at the same time. Motivated by the observation that early incorporation of constraints into query graphs can more effectively prune the search space, we propose a modified staged query graph generation method with more flexible ways to generate query graphs. Our experiments clearly show that our method achieves the state of the art on three benchmark KBQA datasets. 2020-07-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/5271 info:doi/10.18653/v1/2020.acl-main.91 https://ink.library.smu.edu.sg/context/sis_research/article/6274/viewcontent/7._Query_Graph_Generation_for_Answering_Multi_hop_Complex_Questions__ACL2020_.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Artificial Intelligence and Robotics Theory and Algorithms |
institution |
Singapore Management University |
building |
SMU Libraries |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
SMU Libraries |
collection |
InK@SMU |
language |
English |
topic |
Artificial Intelligence and Robotics Theory and Algorithms |
spellingShingle |
Artificial Intelligence and Robotics Theory and Algorithms LAN, Yunshi Jing JIANG, Query graph generation for answering multi-hop complex questions from knowledge bases |
description |
Previous work on answering complex questions from knowledge bases usually separately addresses two types of complexity: questions with constraints and questions with multiple hops of relations. In this paper, we handle both types of complexity at the same time. Motivated by the observation that early incorporation of constraints into query graphs can more effectively prune the search space, we propose a modified staged query graph generation method with more flexible ways to generate query graphs. Our experiments clearly show that our method achieves the state of the art on three benchmark KBQA datasets. |
format |
text |
author |
LAN, Yunshi Jing JIANG, |
author_facet |
LAN, Yunshi Jing JIANG, |
author_sort |
LAN, Yunshi |
title |
Query graph generation for answering multi-hop complex questions from knowledge bases |
title_short |
Query graph generation for answering multi-hop complex questions from knowledge bases |
title_full |
Query graph generation for answering multi-hop complex questions from knowledge bases |
title_fullStr |
Query graph generation for answering multi-hop complex questions from knowledge bases |
title_full_unstemmed |
Query graph generation for answering multi-hop complex questions from knowledge bases |
title_sort |
query graph generation for answering multi-hop complex questions from knowledge bases |
publisher |
Institutional Knowledge at Singapore Management University |
publishDate |
2020 |
url |
https://ink.library.smu.edu.sg/sis_research/5271 https://ink.library.smu.edu.sg/context/sis_research/article/6274/viewcontent/7._Query_Graph_Generation_for_Answering_Multi_hop_Complex_Questions__ACL2020_.pdf |
_version_ |
1770575366232997888 |