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We continue the study of the reproducibility of Propp’s annotations from Bod et al. (2012). We present four experiments in which test subjects were taught Propp’s annotation system; we conclude that Propp’s system needs a significant amount of training, but that with sufficient time investment, it can be reliably trained for simple tales.
We present a technique called event mapping that allows to project text representations into event lists, produce an event table, and derive quantitative conclusions to compare the text representations. The main application of the technique is the case where two classes of text representations have been collected in two different settings (e.g., as annotations in two different formal frameworks) and we can compare the two classes with respect to their systematic differences in the event table. We illustrate how the technique works by applying it to data collected in two experiments (one using annotations in Vladimir Propp’s framework, the other using natural language summaries).
This paper discusses the semi-formal language of mathematics and presents the Naproche CNL, a controlled natural language for mathematical authoring. Proof Representation Structures, an adaptation of Discourse Representation Structures, are used to represent the semantics of texts written in the Naproche CNL. We discuss how the Naproche CNL can be used in formal mathematics, and present our prototypical Naproche system, a computer program for parsing texts in the Naproche CNL and checking the proofs in them for logical correctness.