Name
Abstract | ||
|---|---|---|
Disambiguating named entities in natural-language text maps mentions of ambiguous names onto canonical entities like people or places, registered in a knowledge base such as DBpedia or YAGO. This paper presents a robust method for collective disambiguation, by harnessing context from knowledge bases and using a new form of coherence graph. It unifies prior approaches into a comprehensive framework that combines three measures: the prior probability of an entity being mentioned, the similarity between the contexts of a mention and a candidate entity, as well as the coherence among candidate entities for all mentions together. The method builds a weighted graph of mentions and candidate entities, and computes a dense subgraph that approximates the best joint mention-entity mapping. Experiments show that the new method significantly outperforms prior methods in terms of accuracy, with robust behavior across a variety of inputs. |
Year | Venue | Keywords |
|---|---|---|
2011 | EMNLP | coherence graph,prior probability,knowledge base,robust method,prior method,candidate entity,new method,new form,robust disambiguation,canonical entity,prior approach |
Field | DocType | Volume |
Entity linking,Graph,Information retrieval,Computer science,Coherence (physics),Natural language processing,Artificial intelligence,Knowledge base,Prior probability,Machine learning | Conference | D11-1 |
Citations | PageRank | References |
368 | 11.36 | 25 |
Authors | ||
9 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Johannes Hoffart | 1 | 1362 | 52.62 |
| Mohamed Amir Yosef | 2 | 499 | 18.42 |
| Ilaria Bordino | 3 | 629 | 28.81 |
| Hagen Fürstenau | 4 | 533 | 20.43 |
| Manfred Pinkal | 5 | 1116 | 69.77 |
| Marc Spaniol | 6 | 897 | 61.13 |
| Bilyana Taneva | 7 | 410 | 14.37 |
| Stefan Thater | 8 | 756 | 38.54 |
| Gerhard Weikum | 9 | 12710 | 2146.01 |