NorNE: Annotating Named Entities for Norwegian
This provides a resource for NLP researchers working on Norwegian, but it is incremental as it builds on existing annotations.
The authors tackled the lack of a manually annotated named entity corpus for Norwegian by creating NorNE, which extends an existing treebank with around 600,000 tokens and rich entity types, and they evaluated it using a neural sequence labeling model.
This paper presents NorNE, a manually annotated corpus of named entities which extends the annotation of the existing Norwegian Dependency Treebank. Comprising both of the official standards of written Norwegian (Bokmål and Nynorsk), the corpus contains around 600,000 tokens and annotates a rich set of entity types including persons, organizations, locations, geo-political entities, products, and events, in addition to a class corresponding to nominals derived from names. We here present details on the annotation effort, guidelines, inter-annotator agreement and an experimental analysis of the corpus using a neural sequence labeling architecture.