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

Understand

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 (HRL), but these do not extend well to low-resource languages (LRL) with few, if any, Wikipedia pages.
• Recently, transfer learning methods have been shown to reduce the demand for resources in the LRL by utilizing resources in closely-related languages, but the performance still lags far behind their high-resource counterparts.