In this paper, we present a workbench for semi-automatic ontology population from textual documents. It provides an environment for mapping the linguistic extractions with the domain ontology thanks to knowledge acquisition rules. Those rules are activated when a pertinent linguistic tag is reached. Those linguistic tags are then mapped to a concept, one of its attributes or even a semantic relation between several concepts. The rules instantiate these concepts, attributes and relations in the knowledge base constrained by the domain ontology. This paper deals with the underlying knowledge capture process and presents the first experiments realized on a real client application from the legal publishing domain.
Temporal expressions that refer to a part of a calendar area in terms of common calendar divisions are studied. Our claim is that such a "calendar expression" (CE) can be described by a succession of operators operating on a calendar base (CB). These operators are categorized: a pointing operator that transform a CB into a CE; a focalizing/shifting operator that reduces or shifts the CE into another CE, and finally a zoning operator that provides the wanted CE from this last CE. Relying on these operators, a set of annotations is presented which are used to automatically annotate biographic texts. A software application, plugged in the platform Navitext, is described that builds a calendar view of a biographic text.
How can researchers identify suitable research data repositories for the deposit of their research data? Which repository matches best the technical and legal requirements of a specific research project? For this end and with a humanities perspective the Data Deposit Recommendation Service (DDRS) has been developed as a prototype. It not only serves as a functional service for selecting humanities research data repositories but it is particularly a technical demonstrator illustrating the potential of re-using an already existing infrastructure - in this case re3data - and the feasibility to set up this kind of service for other research disciplines. The documentation and the code of this project can be found in the DARIAH GitHub repository: https://dariah-eric.github.io/ddrs/.
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