In plain words: A collection of 41,000 sentences labeled with 34 relationship types between people teaches systems to spot how two people are connected in text. It is the first dataset for this job, with three test tasks and starter systems to compare against.
Abstract · IPRE: a Dataset for Inter-Personal Relationship Extraction
Inter-personal relationship is the basis of human society. In order to automatically identify the relations between persons from texts, we need annotated data for training systems. However, there is a lack of a massive amount of such data so far. To address this situation, we introduce IPRE, a new dataset for inter-personal relationship extraction which aims to facilitate information extraction and knowledge graph construction research. In total, IPRE has over 41,000 labeled sentences for 34 types of relations, including about 9,000 sentences annotated by workers. Our data is the first dataset for inter-personal relationship extraction. Additionally, we define three evaluation tasks based on IPRE and provide the baseline systems for further comparison in future work.
Haitao Wang, Zhengqiu He, Jin Ma, Wenliang Chen, Min Zhang
arXiv:1907.12801 · cs.CL · submitted Jul 30, 2019 · updated Aug 10, 2019
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