2016 AutomaticConstructionandEvaluat

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Subject Headings: Sew Corpus; Word Embedding System; Wikipedia; Wikipedia-Based Concept Vector.

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Abstract

The hyperlink structure of Wikipedia constitutes a key resource for many Natural Language Processing tasks and applications, as it provides several million semantic annotations of entities in context. Yet only a small fraction of mentions across the entire Wikipedia corpus is linked. In this paper we present the automatic construction and evaluation of a Semantically Enriched Wikipedia in which the overall number of linked mentions has been more than tripled solely by exploiting the structure of Wikipedia itself and the wide-coverage sense inventory of BabelNet. As a result we obtain a sense-annotated corpus with more than 200 million annotations of over 4 million different concepts and named entities. We then show that our corpus leads to competitive results on multiple tasks, such as Entity Linking and Word Similarity.

References

BibTeX

@inproceedings{2016_AutomaticConstructionandEvaluat,
  author    = {Alessandro Raganato and
               Claudio Delli Bovi and
               Roberto Navigli},
  editor    = {Subbarao Kambhampati},
  title     = {Automatic Construction and Evaluation of a Large Semantically Enriched
               Wikipedia},
  booktitle = {Proceedings of the Twenty-Fifth International Joint Conference on
               Artificial Intelligence (IJCAI 2016)},
  pages     = {2894--2900},
  publisher = {IJCAI/AAAI Press},
  year      = {2016},
  url       = {http://www.ijcai.org/Abstract/16/411},
}


 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2016 AutomaticConstructionandEvaluatAlessandro Raganato
Claudio Delli Bovi
Roberto Navigli
Automatic Construction and Evaluation of a Large Semantically Enriched Wikipedia2016