• DOI:10.1162/tacl_a_00303
Corpus ID: 211818155

Improving Candidate Generation for Low-resource Cross-lingual Entity Linking

@article{Zhou2020ImprovingCG,
  title={Improving Candidate Generation for Low-resource Cross-lingual Entity Linking},
  author={Shuyan Zhou and Shruti Rijhawani and J. Wieting and J. Carbonell and Graham Neubig},
  journal={Transactions of the Association for Computational Linguistics},
  year={2020},
  volume={8},
  pages={109-124}
}

Shuyan Zhou, Shruti Rijhawani, +2 authors Graham Neubig

Published 2020

Computer Science

Transactions of the Association for Computational Linguistics

Cross-lingual entity linking (XEL) is the task of finding referents in a target-language knowledge base (KB) for mentions extracted from source-language texts. The first step of (X)EL is candidate generation, which retrieves a list of plausible candidate entities from the target-language KB for each mention. Approaches based on resources from Wikipedia have proven successful in the realm of relatively high-resource languages, but these do not extend well to low-resource languages with few, if… CONTINUE READING

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