Establishing a New State-of-the-Art for French Named Entity Recognition
This work addresses a gap in resources for French NLP tasks, providing a dataset that could improve applications like information extraction, but it is incremental as it builds upon existing annotations.
The researchers tackled the lack of a large-scale French corpus with named entity and referential annotations by manually annotating the French TreeBank, resulting in a new dataset that includes type, span, and referential information for named entities.
The French TreeBank developed at the University Paris 7 is the main source of morphosyntactic and syntactic annotations for French. However, it does not include explicit information related to named entities, which are among the most useful information for several natural language processing tasks and applications. Moreover, no large-scale French corpus with named entity annotations contain referential information, which complement the type and the span of each mention with an indication of the entity it refers to. We have manually annotated the French TreeBank with such information, after an automatic pre-annotation step. We sketch the underlying annotation guidelines and we provide a few figures about the resulting annotations.