Abstract This paper introduces , a new semantic role labeling method that transforms text into frame-oriented knowledge graph. It performs dependency parsing, identifies the words evoke lexical frames, locates roles and fillers for each frame, runs coercion techniques, formalizes results as formal representation complies with frame semantics used in Framester, factual-linguistic linked data res...

We present a general framework for semantic role labeling. The framework combines a machine learning technique with an integer linear programming based inference procedure, which incorporates linguistic and structural constraints into a global decision process. Within this framework, we study the role of syntactic parsing information in semantic role labeling. We show that full syntactic parsin...

Rapid damage assessment after natural disasters (e.g. earthquakes, floods) and violent conflicts (e.g. war-related destruction) is crucial for initiating effective emergency response actions. Remote sensing satellites equipped with multispectral and Synthetic Aperture Radar (SAR) imaging sensors can provide vital information due to their ability to map affected areas of interest with high geome...