Haotian Chen


Contextualized End-to-End Neural Entity Linking
Haotian Chen | Xi Li | Andrej Zukov Gregoric | Sahil Wadhwa
Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing

We propose an entity linking (EL) model that jointly learns mention detection (MD) and entity disambiguation (ED). Our model applies task-specific heads on top of shared BERT contextualized embeddings. We achieve state-of-the-art results across a standard EL dataset using our model; we also study our model’s performance under the setting when hand-crafted entity candidate sets are not available and find that the model performs well under such a setting too.