UHop: An Unrestricted-Hop Relation Extraction Framework for
Knowledge-Based Question Answering
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by
Zi-Yuan Chen, Chih-Hung Chang, Yi-Pei Chen, Jijnasa Nayak, Lun-Wei Ku
2019
Abstract
In relation extraction for knowledge-based question answering, searching from
one entity to another entity via a single relation is called "one hop". In
related work, an exhaustive search from all one-hop relations, two-hop
relations, and so on to the max-hop relations in the knowledge graph is
necessary but expensive. Therefore, the number of hops is generally restricted
to two or three. In this paper, we propose UHop, an unrestricted-hop framework
which relaxes this restriction by use of a transition-based search framework to
replace the relation-chain-based search one. We conduct experiments on
conventional 1- and 2-hop questions as well as lengthy questions, including
datasets such as WebQSP, PathQuestion, and Grid World. Results show that the
proposed framework enables the ability to halt, works well with
state-of-the-art models, achieves competitive performance without exhaustive
searches, and opens the performance gap for long relation paths.
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