Combining Textual and Graph-Based Features for Named Entity Disambiguation Using Undirected Probabilistic Graphical Models

@inproceedings{Hakimov2016CombiningTA,
  title={Combining Textual and Graph-Based Features for Named Entity Disambiguation Using Undirected Probabilistic Graphical Models},
  author={Sherzod Hakimov and Hendrik ter Horst and Soufian Jebbara and Matthias Hartung and Philipp Cimiano},
  booktitle={EKAW},
  year={2016}
}
Named Entity Disambiguation NED is the task of disambiguating named entities in a natural language text by linking them to their corresponding entities in a knowledge base such as DBpedia, which are already recognized. It is an important step in transforming unstructured text into structured knowledge. Previous work on this task has proven a strong impact of graph-based methods such as PageRank on entity disambiguation. Other approaches rely on distributional similarity between an article and… CONTINUE READING
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