
This paper describes the system developed at the University of the Basque Country (UBC) for the Entity Recognition and Disambiguation Challenge (ERD 2014). We developed a single system for both long and short tracks. We implemented a very basic mention detection component and complement it with a strong disambiguation step, based on Personalized PageRank algorithm. The result and confidence of the disambiguation step is used to decide whether a mention has to be linked, that is, we only link mentions if the disambiguation algorithm is confident enough. This simple method obtained good results in the ERD challenge, reaching the top 10 for both tracks.
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 2 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
