HAMNER: Headword Amplified Multi-span Distantly Supervised Method for Domain Specific Named Entity Recognition

Understand

To tackle Named Entity Recognition (NER) tasks, supervised methods need to obtain sufficient cleanly annotated data, which is labor and time consuming.

• On the contrary, distantly supervised methods acquire automatically annotated data using dictionaries to alleviate this requirement.
• Unfortunately, dictionaries hinder the effectiveness of distantly supervised methods for NER due to its limited coverage, especially in specific domains.
• In this paper, we aim at the limitations of the dictionary usage and mention boundary detection.