Regex Queries over Incomplete Knowledge Bases
release_c3f6m437pvarzffdggvovzvmka
by
Vaibhav Adlakha, Parth Shah, Srikanta Bedathur, Mausam
2021
Abstract
We propose the novel task of answering regular expression queries (containing
disjunction (∨) and Kleene plus (+) operators) over incomplete KBs. The
answer set of these queries potentially has a large number of entities, hence
previous works for single-hop queries in KBC that model a query as a point in
high-dimensional space are not as effective. In response, we develop RotatE-Box
– a novel combination of RotatE and box embeddings. It can model more
relational inference patterns compared to existing embedding based models.
Furthermore, we define baseline approaches for embedding based KBC models to
handle regex operators. We demonstrate performance of RotatE-Box on two new
regex-query datasets introduced in this paper, including one where the queries
are harvested based on actual user query logs. We find that our final
RotatE-Box model significantly outperforms models based on just RotatE and just
box embeddings.
In text/plain
format
Archived Content
There are no accessible files associated with this release. You could check other releases for this work for an accessible version.
Know of a fulltext copy of on the public web? Submit a URL and we will archive it
2005.00480v2
access all versions, variants, and formats of this works (eg, pre-prints)