Zero-Resource Cross-Domain Named Entity Recognition

Understand

Existing models for cross-domain named entity recognition (NER) rely on numerous unlabeled corpus or labeled NER training data in target domains.

• However, collecting data for low-resource target domains is not only expensive but also time-consuming.
• Hence, we propose a cross-domain NER model that does not use any external resources.
• We first introduce a Multi-Task Learning (MTL) by adding a new objective function to detect whether tokens are named entities or not.