Publications
Authors:
  • Alexandr Chernov , Nikolaos Lagos , Matthias Gallé , Agnes Sandor
Citation:
WWW Conference, Montréal, Canada, April 11-15, 2016.
Abstract:
The World Wide Web contains a large number of community
created knowledge of instructional nature. Similarly, in
a commercial setting, databases of instructions are used by
customer-care providers to guide clients in the resolution of
issues. Most of these instructions are expressed in natural
language. Knowledge Bases including such information are
valuable through the sum of their single entries. However,
as each entry is created mostly independently, users (e.g.
other community members) cannot take advantage of the
accumulated knowledge that can be developed via the aggregation
of related entries. In this paper we consider the
problem of inter-linking Knowledge Base entries, in order to
get relevant information from other parts of the Knowledge
Base.
To achieve this, we propose to detect actionable phrases
{ text fragments that describe how to perform a certain
action { and link them to other entries. The extraction
method that we implement achieves an F-score of 67.35%.
We also show that using actionable phrases results in better
linking quality than using coarser-grained spans of text, as
proposed in the literature. Besides the evaluation of both
steps, we also include a detailed error analysis and release our annotation to the community.
Year:
2016
Report number:
2016/015