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Enriching How-to Guides by Linking Actionable Phrases

Alexandr Chernov, Nikolaos Lagos, Matthias Gallé, Agnes Sandor
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.
WWW Conference, Montréal, Canada, April 11-15, 2016.