Name
Abstract | ||
|---|---|---|
Named Entity Disambiguation (NED) systems perform well on news articles and other texts covering a specific time interval. However, NED quality drops when inputs span long time periods like in archives or historic corpora. This paper presents the first time-aware method for NED that resolves ambiguities even when mention contexts give only few cues. The method is based on computing temporal signatures for entities and comparing these to the temporal contexts of input mentions. Our experiments show superior quality on a newly created diachronic corpus.(1) |
Year | Venue | Field |
|---|---|---|
2018 | PROCEEDINGS OF THE 56TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, VOL 2 | Entity linking,Computer science,Artificial intelligence,Natural language processing |
DocType | Volume | Citations |
Conference | P18-2 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Prabal Agarwal | 1 | 0 | 0.34 |
| Jannik Strötgen | 2 | 492 | 38.20 |
| Luciano Del Corro | 3 | 147 | 6.91 |
| Johannes Hoffart | 4 | 1362 | 52.62 |
| Gerhard Weikum | 5 | 12710 | 2146.01 |