The ModelSEN project seeks to model the evolution and development of knowledge systems via a network theoretic approach that encompasses three different layers of so-called socio-epistemic networks: social, semiotic, and semantic. The semiotic and semantic layers are often based on information encoded in large unstructured text corpora, such as scientific publications. One challenge regarding this kind of input is the transition from unstructured explicit and implicit references to structured ones. Using publications of Hans-Jürgen Treder – one of the most prominent scientists of the GDR – as an ego-centred dataset, we are interested in mapping referenced person-names (implicit citations within a textual context) to explicit structured references, thus enabling the application of network analytic methods at the semiotic level. We are interested in the following questions: How can referenced names in a textual context be mapped to explicit publications? Is this mapping more feasible if the names refer to references explicitly cited in the same corpus? Is mapping easier if a name is frequently referenced implicitly but only one explicit publication of the person is referenced in the entire corpus?