Papers by Stefan Schlobach

1 papers
Systematic Study of Long Tail Phenomena in Entity Linking (C18-1)

Copied to clipboard

Challenge: Existing systems for entity linking are based on frequent 'head' cases, while performance drops when moving towards rare 'long tail' entities.
Approach: They propose to use a long tail to investigate the properties of entity linking datasets.
Outcome: The proposed systems overfit to popular/frequent and non-ambiguous cases and find the most difficult cases among the infrequent candidates of ambiguous forms.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations