Abstract
As the previous chapters have shown, the possible ways of representing linguistic data as a graph are as diverse as the data itself. For the process of graph modeling, the decision as to what information will be represented as nodes and what information as relations is of great importance. In addition, what kind of added value is going to be expected by the representation of the data as a graph and what kinds of scientific questions should be answerable by the model.
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Stührenberg, M., Diewald, N., Gleim, R. (2016). Considerations for a Linguistic Network Markup Language. In: Mehler, A., Lücking, A., Banisch, S., Blanchard, P., Job, B. (eds) Towards a Theoretical Framework for Analyzing Complex Linguistic Networks. Understanding Complex Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-47238-5_14
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