LOW-RESOURCE XEL

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Papers with low-resource XEL

TACL

2020.tacl-1

in-KB
Cross-lingual entity linking
XEL
KB
transfer learning methods
entity candidate generation methods
robustness
Top-30 gold candidate recall
low-resource XEL
end-to-end XEL.1

2020

Responsible & Trustworthy NLP

1 papers

Improving Candidate Generation for Low-resource Cross-lingual Entity Linking (2020.tacl-1)

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Shuyan Zhou, Shruti Rijhwani, John Wieting, Jaime Carbonell, Graham Neubig

Responsible & Trustworthy NLP

Challenge:	Existing approaches to cross-lingual entity linking (XEL) do not extend well to low-resource languages with few Wikipedia pages.
Approach:	They propose to improve the model by combining Wikipedia references with a list of plausible candidate entities.
Outcome:	The proposed method yields 16.9% in Top-30 gold candidate recall compared with state-of-the-art models.

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