Reconstruction of Semantic Relationships from Their Projections in Biomolecular Domain

The extraction of nested, semantically rich relationships of biological entities has recently gained popularity in the biomedical text mining community. To move toward this objective, a method is proposed for reconstructing original semantic relationship graphs from projections, where each node and edge is mapped to the representative of its equivalence class, by determining the relationship argument combinations that represent real relationships. It generalises the limited postprocessing step of the method of Björne et al. (2010) and hence extends this extraction method to arbitrarily deep relationships with unrestricted primary argument combinations. The viability of the method is shown by successfully extracting nested relationships in BioInfer and the corpus of the BioNLP’09 Shared Task on Event Extraction. The reported results, to the best of our knowledge, are the first for the nested relationships in BioInfer on a task in which only named entities are given.