@inproceedings{WiegandRothLasarcyketal.2019, author = {Michael Wiegand and Benjamin Roth and Eva Lasarcyk and Stephanie K{\"o}ser and Dietrich Klakow}, title = {A Gold Standard for Relation Extraction in the Food Domain}, series = {Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12), May 21-27, 2012, Istanbul, Turkey}, editor = {Nicoletta Calzolari and Khalid Choukri and Thierry Declerck and Mehmet Uğur Doğan and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis}, publisher = {European Language Resources Association}, address = {Paris}, isbn = {978-2-9517408-7-7}, url = {https://nbn-resolving.org/urn:nbn:de:bsz:mh39-84454}, pages = {507 -- 514}, year = {2019}, abstract = {We present a gold standard for semantic relation extraction in the food domain for German. The relation types that we address are motivated by scenarios for which IT applications present a commercial potential, such as virtual customer advice in which a virtual agent assists a customer in a supermarket in finding those products that satisfy their needs best. Moreover, we focus on those relation types that can be extracted from natural language text corpora, ideally content from the internet, such as web forums, that are easy to retrieve. A typical relation type that meets these requirements are pairs of food items that are usually consumed together. Such a relation type could be used by a virtual agent to suggest additional products available in a shop that would potentially complement the items a customer has already in their shopping cart. Our gold standard comprises structural data, i.e. relation tables, which encode relation instances. These tables are vital in order to evaluate natural language processing systems that extract those relations.}, language = {en} }