The project heureCLÉA aims for the development of a so-called “digital heuristic”– a functional module that supports literary scholars in interpreting and annotating texts. To achieve this, the module “learns” from human-made annotation in order to progress toward an automated generation of textual markup. In our project we explore this approach by way of example: the semantic analysis of time-related phenomena in narrative texts. We envisage the following three phases of development:
automation of markup-tasks of low complexity
exploration and analysis of more complex, manually as well as automatically generated markup versions
computer-aided modeling and generation of markup versions
Within this framework we develop a digital heuristic that offers the user automated procedures for textual analysis. These procedures shall generate markup suggestions that can then be validated by human users. To create its output, the system dynamically deduces probabilistic rules for interpretation and annotation from manually created markup. This heuristic module will finally be integrated into a web-based application that enables the creation of non-deterministic, collaborative textual markup.