RailwayReq Corpus (Q6709269)

Please cite as: Perko, A., Zhao, H. Wotawa, F. (2023). Optimizing Named Entity Recognition for Improving Logical Formulae Abstraction from Technical Requirements Documents. In 2023 10th International Conference on Dependable Systems and Their Applications (DSA) (pp. 211-222). IEEE. https://ieeexplore.ieee.org/document/10314370 Dataset published alongside the paper: "Optimizing Named Entity Recognition for Improving Logical Formulae Abstraction from Technical Requirements Documents". This is a domain-specific NER corpus compiled from technical requirements documents published by the European Unions' railway agency [1], which are also part of the PURE data set of publicly available requirements documents [2]. This corpus was annotated to extract named entities for the generation of predicate-argument structres as used in logical formalisms. [1] European Union agency for railways. URL https://www.era.europa.eu [2] Ferrari, A., Spagnolo, G. O., Gnesi, S. (2017, September). PURE: A dataset of public requirements documents. In2017 IEEE 25th International Requirements Engineering Conference (RE)(pp. 502-505). IEEE.