FrameNet automatic analysis : a study on a French corpus of encyclopedic texts
This work addresses frame analysis for French encyclopedic texts, but it is incremental as it applies an existing method to a new dataset.
The authors tackled automatic frame analysis on a French encyclopedic history corpus using FrameNet, employing an integrated sequence labeling model for joint optimization of frame identification and semantic role tasks, achieving detailed evaluations on feature selection and data complexity.
This article presents an automatic frame analysis system evaluated on a corpus of French encyclopedic history texts annotated according to the FrameNet formalism. The chosen approach relies on an integrated sequence labeling model which jointly optimizes frame identification and semantic role segmentation and identification. The purpose of this study is to analyze the task complexity from several dimensions. Hence we provide detailed evaluations from a feature selection point of view and from the data point of view.