Abstract
This chapter aims to show the uses of modelling alchemical terms in a digital thesaurus using the example of Michael Maier’s (1568-1622) writings. Alchemical language is supposed to be full of secrets and it is indeed full of ambiguities. They are revealed to initiated adepts (‘experts’) who are familiar with the underlying semiotic codes of analogy. Its allegories have wrongly brought alchemy the miscredit of being known as an ‘esoteric pseudo-chemistry’, which recent studies have proven wrong. Alchemical language is an example of scientia poetica; its Decknamen are coded, ornate and unstable. Computational methods like Natural Language Processing (NLP), Named Entity Recognition (NER) and knowledge representation technologies, for example using thesauri of terms of alchemy in XML, allow us to handle the typical ambiguity of alchemical data. We can make implicit instances of knowledge explicit in a digital thesaurus while the linking of a concrete word (a string or label) in a text to the thesaurus remains loose enough to allow for imprecise poetic language. Computational models are “temporary states in a process of coming to know”, in which computers are not “knowledge jukeboxes” but “representation machines” (McCarty). They create a systematic approximation of reality, and from its shortcomings we learn about the reality we aimed to model. This might be a viable and helpful new approach in research on alchemy, a field which has shown a great reluctance to make meaning explicit in the past. But it also comes with the responsibility of ensuring that annotation remains as objective as possible, open to uncertainty and not too concrete in case of ambiguities. The main challenges are linking concepts and labels, and avoiding interpretation in the process of making information explicit, since the annotation will be done automatically.
