Entity-Linking via Graph-Distance Minimization

Roi Blanco
(Yahoo! Research Barcelona, Spain)
Paolo Boldi
(Dipartimento di informatica, Università degli Studi di Milano)
Andrea Marino
(Dipartimento di informatica, Università degli Studi di Milano)

Entity-linking is a natural-language–processing task that consists in identifying the entities mentioned in a piece of text, linking each to an appropriate item in some knowledge base; when the knowledge base is Wikipedia, the problem comes to be known as wikification (in this case, items are wikipedia articles). One instance of entity-linking can be formalized as an optimization problem on the underlying concept graph, where the quantity to be optimized is the average distance between chosen items. Inspired by this application, we define a new graph problem which is a natural variant of the Maximum Capacity Representative Set. We prove that our problem is NP-hard for general graphs; nonetheless, under some restrictive assumptions, it turns out to be solvable in linear time. For the general case, we propose two heuristics: one tries to enforce the above assumptions and another one is based on the notion of hitting distance; we show experimentally how these approaches perform with respect to some baselines on a real-world dataset.

In Dragan Bošnački, Stefan Edelkamp, Alberto Lluch Lafuente and Anton Wijs: Proceedings 3rd Workshop on GRAPH Inspection and Traversal Engineering (GRAPHITE 2014), Grenoble, France, 5th April 2014, Electronic Proceedings in Theoretical Computer Science 159, pp. 30–43.
The second and third authors were supported by the EU-FET grant NADINE (GA 288956)
Published: 29th July 2014.

ArXived at: http://dx.doi.org/10.4204/EPTCS.159.4 bibtex PDF
References in reconstructed bibtex, XML and HTML format (approximated).
Comments and questions to: eptcs@eptcs.org
For website issues: webmaster@eptcs.org