To help researchers investigate relation extraction, we’re releasing a human-judged dataset of two relations about public figures on Wikipedia: nearly 10,000 examples of “place of birth”, and over 40,000 examples of “attended or graduated from an institution”. Each of these was judged by at least 5 raters, and can be used to train or evaluate relation extraction systems. We also plan to release more relations of new types in the coming months.
This is the home page of the ParsCit project, which performs reference string parsing, sometimes also called citation parsing or citation extraction. It is architected as a supervised machine learning procedure that uses Conditional Random Fields as its learning mechanism. You can download the code below, parse strings online, or send batch jobs to our web service (coming soon!). The code contains both the training data, feature generator and shell scripts to connect the system to a web service (used here too).
S. Auer, and J. Lehmann. The Semantic Web: Research and Applications, 4th European Semantic Web Conference, ESWC 2007, Innsbruck, Austria, volume 4519 of Lecture Notes in Computer Science, Springer, Berlin, (2007)
J. Illig, B. Roth, and D. Klakow. Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, volume 2: Short Papers, page 100--105. Gothenburg, Sweden, Association for Computational Linguistics, (April 2014)